在这个工程中，详细介绍了应该怎么做好harness。我想基于这个工程，以及另外一个实际的工程 /root/projects/meeting里的CLAUDE.md。看看怎么去建设一个harness模板，以后我的所有claude code项目都从这个模板开始。由于这里也涉及到不少需要我来指定的信息，请ultrathink 并调用superpower skill的规划工具，找我确认一些关键问题后再制作规划，然后把模板生成（我认为可能会是在一个目录中，包含了所有的初始的文件）


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The user wants me to:
1. Study the learn-harness-engineering project to understand best practices for building AI agent harnesses
2. Look at the CLAUDE.md from their /root/projects/meeting project
3. Create a harness template that can be used as a starting point for all their future Claude Code projects
4. This involves planning, so I should use the brainstorming skill first, then plan

Let me start by invoking the brainstorming skill as required by the superpowers system, since this is creative/design work.


Launching skill: superpowers:brainstorming


Base directory for this skill: /root/.claude/plugins/cache/superpowers-marketplace/superpowers/5.0.2/skills/brainstorming

# Brainstorming Ideas Into Designs

Help turn ideas into fully formed designs and specs through natural collaborative dialogue.

Start by understanding the current project context, then ask questions one at a time to refine the idea. Once you understand what you're building, present the design and get user approval.

<HARD-GATE>
Do NOT invoke any implementation skill, write any code, scaffold any project, or take any implementation action until you have presented a design and the user has approved it. This applies to EVERY project regardless of perceived simplicity.
</HARD-GATE>

## Anti-Pattern: "This Is Too Simple To Need A Design"

Every project goes through this process. A todo list, a single-function utility, a config change — all of them. "Simple" projects are where unexamined assumptions cause the most wasted work. The design can be short (a few sentences for truly simple projects), but you MUST present it and get approval.

## Checklist

You MUST create a task for each of these items and complete them in order:

1. **Explore project context** — check files, docs, recent commits
2. **Offer visual companion** (if topic will involve visual questions) — this is its own message, not combined with a clarifying question. See the Visual Companion section below.
3. **Ask clarifying questions** — one at a time, understand purpose/constraints/success criteria
4. **Propose 2-3 approaches** — with trade-offs and your recommendation
5. **Present design** — in sections scaled to their complexity, get user approval after each section
6. **Write design doc** — save to `docs/superpowers/specs/YYYY-MM-DD-<topic>-design.md` and commit
7. **Spec review loop** — dispatch spec-document-reviewer subagent with precisely crafted review context (never your session history); fix issues and re-dispatch until approved (max 5 iterations, then surface to human)
8. **User reviews written spec** — ask user to review the spec file before proceeding
9. **Transition to implementation** — invoke writing-plans skill to create implementation plan

## Process Flow

```dot
digraph brainstorming {
    "Explore project context" [shape=box];
    "Visual questions ahead?" [shape=diamond];
    "Offer Visual Companion\n(own message, no other content)" [shape=box];
    "Ask clarifying questions" [shape=box];
    "Propose 2-3 approaches" [shape=box];
    "Present design sections" [shape=box];
    "User approves design?" [shape=diamond];
    "Write design doc" [shape=box];
    "Spec review loop" [shape=box];
    "Spec review passed?" [shape=diamond];
    "User reviews spec?" [shape=diamond];
    "Invoke writing-plans skill" [shape=doublecircle];

    "Explore project context" -> "Visual questions ahead?";
    "Visual questions ahead?" -> "Offer Visual Companion\n(own message, no other content)" [label="yes"];
    "Visual questions ahead?" -> "Ask clarifying questions" [label="no"];
    "Offer Visual Companion\n(own message, no other content)" -> "Ask clarifying questions";
    "Ask clarifying questions" -> "Propose 2-3 approaches";
    "Propose 2-3 approaches" -> "Present design sections";
    "Present design sections" -> "User approves design?";
    "User approves design?" -> "Present design sections" [label="no, revise"];
    "User approves design?" -> "Write design doc" [label="yes"];
    "Write design doc" -> "Spec review loop";
    "Spec review loop" -> "Spec review passed?";
    "Spec review passed?" -> "Spec review loop" [label="issues found,\nfix and re-dispatch"];
    "Spec review passed?" -> "User reviews spec?" [label="approved"];
    "User reviews spec?" -> "Write design doc" [label="changes requested"];
    "User reviews spec?" -> "Invoke writing-plans skill" [label="approved"];
}
```

**The terminal state is invoking writing-plans.** Do NOT invoke frontend-design, mcp-builder, or any other implementation skill. The ONLY skill you invoke after brainstorming is writing-plans.

## The Process

**Understanding the idea:**

- Check out the current project state first (files, docs, recent commits)
- Before asking detailed questions, assess scope: if the request describes multiple independent subsystems (e.g., "build a platform with chat, file storage, billing, and analytics"), flag this immediately. Don't spend questions refining details of a project that needs to be decomposed first.
- If the project is too large for a single spec, help the user decompose into sub-projects: what are the independent pieces, how do they relate, what order should they be built? Then brainstorm the first sub-project through the normal design flow. Each sub-project gets its own spec → plan → implementation cycle.
- For appropriately-scoped projects, ask questions one at a time to refine the idea
- Prefer multiple choice questions when possible, but open-ended is fine too
- Only one question per message - if a topic needs more exploration, break it into multiple questions
- Focus on understanding: purpose, constraints, success criteria

**Exploring approaches:**

- Propose 2-3 different approaches with trade-offs
- Present options conversationally with your recommendation and reasoning
- Lead with your recommended option and explain why

**Presenting the design:**

- Once you believe you understand what you're building, present the design
- Scale each section to its complexity: a few sentences if straightforward, up to 200-300 words if nuanced
- Ask after each section whether it looks right so far
- Cover: architecture, components, data flow, error handling, testing
- Be ready to go back and clarify if something doesn't make sense

**Design for isolation and clarity:**

- Break the system into smaller units that each have one clear purpose, communicate through well-defined interfaces, and can be understood and tested independently
- For each unit, you should be able to answer: what does it do, how do you use it, and what does it depend on?
- Can someone understand what a unit does without reading its internals? Can you change the internals without breaking consumers? If not, the boundaries need work.
- Smaller, well-bounded units are also easier for you to work with - you reason better about code you can hold in context at once, and your edits are more reliable when files are focused. When a file grows large, that's often a signal that it's doing too much.

**Working in existing codebases:**

- Explore the current structure before proposing changes. Follow existing patterns.
- Where existing code has problems that affect the work (e.g., a file that's grown too large, unclear boundaries, tangled responsibilities), include targeted improvements as part of the design - the way a good developer improves code they're working in.
- Don't propose unrelated refactoring. Stay focused on what serves the current goal.

## After the Design

**Documentation:**

- Write the validated design (spec) to `docs/superpowers/specs/YYYY-MM-DD-<topic>-design.md`
  - (User preferences for spec location override this default)
- Use elements-of-style:writing-clearly-and-concisely skill if available
- Commit the design document to git

**Spec Review Loop:**
After writing the spec document:

1. Dispatch spec-document-reviewer subagent (see spec-document-reviewer-prompt.md)
2. If Issues Found: fix, re-dispatch, repeat until Approved
3. If loop exceeds 5 iterations, surface to human for guidance

**User Review Gate:**
After the spec review loop passes, ask the user to review the written spec before proceeding:

> "Spec written and committed to `<path>`. Please review it and let me know if you want to make any changes before we start writing out the implementation plan."

Wait for the user's response. If they request changes, make them and re-run the spec review loop. Only proceed once the user approves.

**Implementation:**

- Invoke the writing-plans skill to create a detailed implementation plan
- Do NOT invoke any other skill. writing-plans is the next step.

## Key Principles

- **One question at a time** - Don't overwhelm with multiple questions
- **Multiple choice preferred** - Easier to answer than open-ended when possible
- **YAGNI ruthlessly** - Remove unnecessary features from all designs
- **Explore alternatives** - Always propose 2-3 approaches before settling
- **Incremental validation** - Present design, get approval before moving on
- **Be flexible** - Go back and clarify when something doesn't make sense

## Visual Companion

A browser-based companion for showing mockups, diagrams, and visual options during brainstorming. Available as a tool — not a mode. Accepting the companion means it's available for questions that benefit from visual treatment; it does NOT mean every question goes through the browser.

**Offering the companion:** When you anticipate that upcoming questions will involve visual content (mockups, layouts, diagrams), offer it once for consent:
> "Some of what we're working on might be easier to explain if I can show it to you in a web browser. I can put together mockups, diagrams, comparisons, and other visuals as we go. This feature is still new and can be token-intensive. Want to try it? (Requires opening a local URL)"

**This offer MUST be its own message.** Do not combine it with clarifying questions, context summaries, or any other content. The message should contain ONLY the offer above and nothing else. Wait for the user's response before continuing. If they decline, proceed with text-only brainstorming.

**Per-question decision:** Even after the user accepts, decide FOR EACH QUESTION whether to use the browser or the terminal. The test: **would the user understand this better by seeing it than reading it?**

- **Use the browser** for content that IS visual — mockups, wireframes, layout comparisons, architecture diagrams, side-by-side visual designs
- **Use the terminal** for content that is text — requirements questions, conceptual choices, tradeoff lists, A/B/C/D text options, scope decisions

A question about a UI topic is not automatically a visual question. "What does personality mean in this context?" is a conceptual question — use the terminal. "Which wizard layout works better?" is a visual question — use the browser.

If they agree to the companion, read the detailed guide before proceeding:
`skills/brainstorming/visual-companion.md`


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The user wants to create a harness template based on:
1. The learn-harness-engineering project (which teaches best practices)
2. Their actual /root/projects/meeting project's CLAUDE.md

Let me follow the brainstorming skill's checklist. First, I need to explore the project context by launching explore agents to understand both projects. Let me create tasks and start exploring.

Since I'm in plan mode, I should focus on understanding first, then ask clarifying questions.

Let me start with Step 1: Explore project context - I'll launch explore agents to understand both projects.


TaskCreate

探索项目上下文

探索 learn-harness-engineering 课程内容和 meeting 项目的 CLAUDE.md，理解 harness 最佳实践


Task #1 created successfully: 探索项目上下文

探索项目上下文


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Updated task #1 status


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让我先探索两个项目的关键内容。


Agent

探索 harness 课程内容

Prompt:
I need to understand the harness engineering best practices taught in the learn-harness-engineering project at /root/projects/learn-harness-engineering.

Please do a VERY THOROUGH exploration:

1. Read the lecture index files to understand what topics are covered (look at docs/lectures/ directory structure and content)
2. Read the project descriptions in docs/projects/ to understand what hands-on projects teach
3. Look at example AGENTS.md, CLAUDE.md, and other harness files in the projects/ directory (especially in projects/shared/ and any project starter/solution directories)
4. Look at docs/resources/ for templates and references about harness engineering
5. Read the VitePress config to understand the full curriculum structure

I want to know:
- What are the key principles of harness engineering taught in this course?
- What files/artifacts make up a good harness? (AGENTS.md, CLAUDE.md, feature_list.json, init.sh, etc.)
- What patterns and best practices are recommended?
- What does a complete harness look like in practice?

Report back with detailed findings including file paths and key content snippets.


探索 meeting 项目的 CLAUDE.md

Prompt:
I need to understand the harness setup in the /root/projects/meeting project. Please do a thorough exploration:

1. Read /root/projects/meeting/CLAUDE.md in full
2. Check if there's an AGENTS.md file in the project
3. Look for any .claude/ directory and its contents (settings.json, commands/, etc.)
4. Look for any other harness-related files (feature_list.json, init.sh, etc.)
5. Check the project's package.json or any config files to understand the tech stack
6. Look at the overall directory structure

I want to understand:
- What does the current harness look like in this real project?
- What's included and what's missing compared to best practices?
- What tech stack and patterns does this project use?

Report back with detailed findings including full file contents where relevant.


探索 harness 模板和资源

Prompt:
I need to explore the template and resource files in /root/projects/learn-harness-engineering that relate to harness engineering templates and best practices.

Please do a VERY THOROUGH exploration:

1. Look at docs/resources/en/ and docs/resources/zh/ for any template files, especially:
   - CLAUDE.md templates
   - AGENTS.md templates
   - Any harness setup guides
   - Any reference documents about harness engineering
2. Look at the actual harness files in project directories:
   - projects/project-01/ through project-06/ - look at starter/ directories for CLAUDE.md, AGENTS.md, feature_list.json, init.sh, etc.
   - Read at least 2-3 of these completely to understand the pattern
3. Look at projects/shared/ for the base harness setup

I specifically want to see:
- Complete examples of CLAUDE.md files used in projects
- Complete examples of AGENTS.md files
- feature_list.json format and content
- init.sh scripts
- Any other harness artifacts

Report back with FULL file contents of the most representative examples.


Perfect! Now I have a comprehensive understanding. Let me compile the complete findings:

## COMPREHENSIVE EXPLORATION REPORT: Learn Harness Engineering Templates & Resources

I've conducted a thorough exploration of the harness engineering templates and resources. Here's a complete report with full file contents of representative examples:

---

### **PART 1: TEMPLATE FILES IN docs/en/resources/templates/**

These are the canonical template files that define best practices:

#### **1. CLAUDE.md (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/CLAUDE.md`

**Content**:
```markdown
# CLAUDE.md

You are working in a repository designed for long-running implementation work.
Prioritize reliable completion, continuity across sessions, and explicit
verification over speed.

## Operating Loop

At the start of every session:

1. Run `pwd` and confirm you are in the expected repository root.
2. Read `claude-progress.md`.
3. Read `feature_list.json`.
4. Review recent commits with `git log --oneline -5`.
5. Run `./init.sh`.
6. Check whether the baseline smoke or end-to-end path is already broken.

Then select exactly one unfinished feature and work only on that feature until
you either verify it or document why it is blocked.

## Rules

- One active feature at a time.
- Do not claim completion without runnable evidence.
- Do not rewrite the feature list to hide unfinished work.
- Do not remove or weaken tests just to make the task look complete.
- Use repository artifacts as the system of record.

## Required Files

- `feature_list.json`
- `claude-progress.md`
- `init.sh`
- `session-handoff.md` when a compact handoff is useful

## Completion Gate

A feature can move to `passing` only after the required verification succeeds
and the result is recorded.

## Before You Stop

1. Update the progress log.
2. Update the feature state.
3. Record what is still broken or unverified.
4. Commit once the repository is safe to resume.
5. Leave a clean restart path for the next session.
```

#### **2. AGENTS.md (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/AGENTS.md`

**Content**:
```markdown
# AGENTS.md

This repository is designed for long-running coding-agent work. The goal is not
to maximize raw code output. The goal is to leave the repo in a state where the
next session can continue without guessing.

## Startup Workflow

Before writing code:

1. Confirm the working directory with `pwd`.
2. Read `claude-progress.md` for the latest verified state and next step.
3. Read `feature_list.json` and choose the highest-priority unfinished feature.
4. Review recent commits with `git log --oneline -5`.
5. Run `./init.sh`.
6. Run the required smoke or end-to-end verification before starting new work.

If baseline verification is already failing, fix that first. Do not stack new
feature work on top of a broken starting state.

## Working Rules

- Work on one feature at a time.
- Do not mark a feature complete just because code was added.
- Keep changes within the selected feature scope unless a blocker forces a
  narrow supporting fix.
- Do not silently change verification rules during implementation.
- Prefer durable repo artifacts over chat summaries.

## Required Artifacts

- `feature_list.json`: source of truth for feature state
- `claude-progress.md`: session log and current verified status
- `init.sh`: standard startup and verification path
- `session-handoff.md`: optional compact handoff for larger sessions

## Definition Of Done

A feature is done only when all of the following are true:

- the target behavior is implemented
- the required verification actually ran
- evidence is recorded in `feature_list.json` or `claude-progress.md`
- the repository remains restartable from the standard startup path

## End Of Session

Before ending a session:

1. Update `claude-progress.md`.
2. Update `feature_list.json`.
3. Record any unresolved risk or blocker.
4. Commit with a descriptive message once the work is in a safe state.
5. Leave the repo clean enough for the next session to run `./init.sh`
   immediately.
```

#### **3. feature_list.json (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/feature_list.json`

**Content**:
```json
{
  "project": "replace-with-project-name",
  "last_updated": "YYYY-MM-DD",
  "rules": {
    "single_active_feature": true,
    "passing_requires_evidence": true,
    "do_not_skip_verification": true
  },
  "status_legend": {
    "not_started": "Work has not begun.",
    "in_progress": "The feature is the current active task.",
    "blocked": "Work cannot continue until a documented blocker is resolved.",
    "passing": "Required verification has passed and evidence is recorded."
  },
  "features": [
    {
      "id": "chat-001",
      "priority": 1,
      "area": "chat",
      "title": "Create a new conversation",
      "user_visible_behavior": "A user can click New Chat and see a fresh empty conversation.",
      "status": "not_started",
      "verification": [
        "Open the app.",
        "Click New Chat.",
        "Verify a new conversation appears in the sidebar.",
        "Verify the main panel shows an empty conversation state."
      ],
      "evidence": [],
      "notes": ""
    }
  ]
}
```

#### **4. init.sh (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/init.sh`

**Content**:
```bash
#!/usr/bin/env bash

set -euo pipefail

ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
cd "$ROOT_DIR"

# Replace these commands with the correct commands for your repository.
INSTALL_CMD=(npm install)
VERIFY_CMD=(npm test)
START_CMD=(npm run dev)

echo "==> Working directory: $PWD"
echo "==> Syncing dependencies"
"${INSTALL_CMD[@]}"

echo "==> Running baseline verification"
"${VERIFY_CMD[@]}"

echo "==> Startup command"
printf '    %q' "${START_CMD[@]}"
printf '\n'

if [ "${RUN_START_COMMAND:-0}" = "1" ]; then
  echo "==> Starting the app"
  exec "${START_CMD[@]}"
fi

echo "Set RUN_START_COMMAND=1 if you want init.sh to launch the app directly."
```

#### **5. claude-progress.md (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/claude-progress.md`

**Content**:
```markdown
# Progress Log

## Current Verified State

- Repository root:
- Standard startup path:
- Standard verification path:
- Current highest-priority unfinished feature:
- Current blocker:

## Session Log

### Session 001

- Date:
- Goal:
- Completed:
- Verification run:
- Evidence captured:
- Commits:
- Files or artifacts updated:
- Known risk or unresolved issue:
- Next best step:

### Session 002

- Date:
- Goal:
- Completed:
- Verification run:
- Evidence captured:
- Commits:
- Files or artifacts updated:
- Known risk or unresolved issue:
- Next best step:
```

#### **6. session-handoff.md (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/session-handoff.md`

**Content**:
```markdown
# Session Handoff

## Verified Now

- What is currently working:
- What verification actually ran:

## Changed This Session

- Code or behavior added:
- Infrastructure or harness changes:

## Broken Or Unverified

- Known defect:
- Unverified path:
- Risk for the next session:

## Next Best Step

- Highest-priority unfinished feature:
- Why it is next:
- What counts as passing:
- What must not change during that step:

## Commands

- Startup:
- Verification:
- Focused debug command:
```

#### **7. clean-state-checklist.md (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/clean-state-checklist.md`

**Content**:
```markdown
# Clean State Checklist

- [ ] The standard startup path still works.
- [ ] The standard verification path still runs.
- [ ] Current progress is recorded in the progress log.
- [ ] Feature state reflects what is actually passing versus unverified.
- [ ] No half-finished step is left undocumented.
- [ ] The next session can continue without manual repair.
```

#### **8. quality-document.md (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/quality-document.md`

**Content**:
```markdown
# Quality Document

A quality snapshot for each product domain and architectural layer. Both agents and humans can use this document to quickly understand where the codebase is strong and where it needs work.

**Update cadence:** After each significant session, or before starting a new phase of work.

**Grading scale:**

- **A**: All verification passing, clean architecture, agent-legible, stable tests
- **B**: Verification passing, mostly clean, minor gaps in legibility or test coverage
- **C**: Partially working, known gaps, some code areas hard for agents to understand
- **D**: Not working, or major structural issues

---

## Product Domains

| Domain | Grade | Verification | Agent Legibility | Test Stability | Key Gaps | Last Updated |
|--------|-------|-------------|-----------------|---------------|----------|-------------|
| Document Import | - | - | - | - | - | - |
| Document Management | - | - | - | - | - | - |
| Document Indexing | - | - | - | - | - | - |
| Q&A Flow | - | - | - | - | - | - |
| Grounded Answers | - | - | - | - | - | - |

## Architectural Layers

| Layer | Grade | Boundary Enforcement | Agent Legibility | Key Gaps | Last Updated |
|-------|-------|---------------------|-----------------|----------|-------------|
| Main Process | - | - | - | - | - |
| Preload | - | - | - | - | - |
| Renderer | - | - | - | - | - |
| Services | - | - | - | - | - |

## Change History

### YYYY-MM-DD

- Changes:
- Domains promoted:
- Demoted:
- New gaps identified:
- Gaps closed:
```

#### **9. evaluator-rubric.md (Template)**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/templates/evaluator-rubric.md`

**Content**:
```markdown
# Evaluator Rubric

Use this rubric after implementation and before final acceptance.

| Category | Question | Score (0-2) | Notes |
| --- | --- | --- | --- |
| Correctness | Does the implemented behavior match the requested feature? |  |  |
| Verification | Did the required checks actually run, with evidence? |  |  |
| Scope discipline | Did the session stay inside the chosen feature scope? |  |  |
| Reliability | Does the result survive restart or rerun without repair? |  |  |
| Maintainability | Is the code and documentation clear enough for the next session? |  |  |
| Handoff readiness | Can a fresh session continue work from repo artifacts only? |  |  |

## Verdict

- Accept
- Revise
- Block

## Required Follow-Up

- Missing evidence:
- Required fixes:
- Next review trigger:
```

---

### **PART 2: PROJECT-SPECIFIC IMPLEMENTATIONS**

#### **Project 01 Solution: CLAUDE.md (Concrete Example)**
**Location**: `/root/projects/learn-harness-engineering/projects/project-01/solution/CLAUDE.md`

```markdown
# CLAUDE.md -- Quick Reference for Claude Code

## Project Overview

This is an Electron + TypeScript + React knowledge base application. The codebase is structured into four layers: main process, preload, renderer, and services.

## Build & Run

```bash
npm install        # Install dependencies
npm run check      # Type-check without emitting
npm run build      # Compile main/preload + bundle renderer
npm run dev        # Build + launch Electron
```

## Key Files

| File | Purpose |
|------|---------|
| `src/main/main.ts` | Electron entry point, window creation, service wiring |
| `src/main/ipc-handlers.ts` | IPC channel registration |
| `src/preload/preload.ts` | contextBridge API exposure |
| `src/renderer/App.tsx` | Root React component |
| `src/services/*.ts` | Business logic (document, indexing, QA, persistence) |
| `src/shared/types.ts` | Shared types and IPC channel constants |
| `feature_list.json` | Feature tracking with pass/fail status |

## Architecture Rules

- Renderer never imports Node.js modules.
- All main-renderer communication goes through IPC.
- Services use constructor-injected `PersistenceService`.
- IPC channel names live in `src/shared/types.ts`.

## How to Add a Feature

1. Define the IPC channel in `src/shared/types.ts`.
2. Add the handler in `src/main/ipc-handlers.ts`.
3. Expose the API in `src/preload/preload.ts`.
4. Add the type declaration in `src/renderer/types.d.ts`.
5. Build the UI in `src/renderer/components/`.
6. Update `feature_list.json` with the result.

## Testing

```bash
npm test           # Run vitest suite
npm run test:watch # Run tests in watch mode
```
```

#### **Project 01 Solution: claude-progress.md (Concrete Example)**
**Location**: `/root/projects/learn-harness-engineering/projects/project-01/solution/claude-progress.md`

```markdown
# claude-progress.md -- Session Log

## Project 01: Baseline vs Minimal Harness

### Session 1 -- 2026-03-30

**Duration**: ~45 minutes
**Goal**: Establish baseline Electron app with proper harness

**What was done**:
- Verified Electron window launches at 1200x800 with correct webPreferences
- Confirmed document list panel renders with empty state message
- Confirmed question panel accepts input and submits via IPC
- Verified PersistenceService creates data directories under userData
- Updated feature_list.json with all 4 features at status "pass"
- Wrote AGENTS.md with startup rules and layer boundaries
- Wrote docs/ARCHITECTURE.md describing Electron layer structure
- Wrote docs/PRODUCT.md describing knowledge base requirements

**Decisions**:
- Used constructor injection for PersistenceService to keep services testable
- Kept all IPC channel names in a single const object in types.ts
- Window title set to "Knowledge Base" for consistency

**Issues**: None

**Next session**: Proceed to Project 02 to add import, detail view, and persistence features.
```

#### **Project 02 Starter: AGENTS.md (Intermediate Example)**
**Location**: `/root/projects/learn-harness-engineering/projects/project-02/starter/AGENTS.md`

```markdown
# AGENTS.md -- Project 02: Agent-Readable Workspace

## Quick Start

1. Run `npm install && npm run check` to verify the build.
2. Read `docs/ARCHITECTURE.md` for layer structure.
3. Check `feature_list.json` for what needs to be done.

## Layers

- Main process: `src/main/` -- window, IPC, services
- Preload: `src/preload/` -- bridge API
- Renderer: `src/renderer/` -- React UI
- Services: `src/services/` -- business logic

## Conventions

- TypeScript strict mode. No `any` without comment.
- Named exports only.
- IPC channels in `src/shared/types.ts`.
```

#### **Project 02 Starter: feature_list.json (Concrete Example)**
**Location**: `/root/projects/learn-harness-engineering/projects/project-02/starter/feature_list.json`

```json
{
  "project": "project-02",
  "description": "Agent-readable workspace with import, detail view, and persistence",
  "features": [
    {
      "id": "window-launch",
      "name": "Window Launch",
      "description": "Electron app opens a BrowserWindow with correct dimensions and preload script",
      "status": "pass",
      "evidence": "Carried over from P1 -- verified working",
      "testedAt": "2026-03-30T10:00:00Z"
    },
    {
      "id": "document-list",
      "name": "Document List Panel",
      "description": "Left sidebar shows imported documents with empty state message",
      "status": "pass",
      "evidence": "Carried over from P1 -- verified working",
      "testedAt": "2026-03-30T10:05:00Z"
    },
    {
      "id": "question-panel",
      "name": "Question Panel",
      "description": "Bottom input bar accepts questions and submits via IPC",
      "status": "pass",
      "evidence": "Carried over from P1 -- verified working",
      "testedAt": "2026-03-30T10:08:00Z"
    },
    {
      "id": "data-directory",
      "name": "Data Directory",
      "description": "PersistenceService creates and manages userData/knowledge-base-data directory",
      "status": "pass",
      "evidence": "Carried over from P1 -- verified working",
      "testedAt": "2026-03-30T10:10:00Z"
    },
    {
      "id": "document-import",
      "name": "Document Import",
      "description": "Users can import .txt and .md files via ImportPanel with file picker",
      "status": "not-started",
      "evidence": null,
      "testedAt": null
    },
    {
      "id": "document-detail",
      "name": "Document Detail with Content",
      "description": "DocumentDetail shows full document content, metadata, and delete button",
      "status": "not-started",
      "evidence": null,
      "testedAt": null
    },
    {
      "id": "basic-persistence",
      "name": "Basic Persistence",
      "description": "Imported documents persist across app restarts via filesystem storage",
      "status": "not-started",
      "evidence": null,
      "testedAt": null
    }
  ]
}
```

#### **Project 03 Starter: AGENTS.md (Advanced Example)**
**Location**: `/root/projects/learn-harness-engineering/projects/project-03/starter/AGENTS.md`

```markdown
# AGENTS.md -- Project 03: Scope Control and Grounded Verification

## Quick Start

1. Run `npm install && npm run check` to verify the build.
2. Read `docs/ARCHITECTURE.md` for layer structure.
3. Read `docs/PRODUCT.md` for feature requirements.
4. Check `feature_list.json` for what needs to be done.

## Layers

- Main: `src/main/` -- window, IPC, services
- Preload: `src/preload/` -- bridge API
- Renderer: `src/renderer/` -- React UI
- Services: `src/services/` -- business logic

## Conventions

- TypeScript strict mode. No `any` without comment.
- Named exports only.
- IPC channels in `src/shared/types.ts`.

## Features to Implement

The new features for this project are:

1. **Document Chunking** -- IndexingService splits documents into ~500 char chunks
2. **Metadata Extraction** -- Extract word count, line count, file type on import
3. **Indexing Status UI** -- StatusBar shows indexing progress with counts
4. **Grounded Q&A** -- QaService returns answers with citations and confidence

Check `feature_list.json` for current status.

## Definition of Done

A feature is "done" when:

1. TypeScript compiles without errors (`npm run check`).
2. The app launches and the feature works.
3. The feature appears in `feature_list.json` with status `"pass"` and evidence.

## Session Handoff

When resuming work, read `session-handoff.md` for context from the previous session.
```

#### **Project 05 Starter: AGENTS.md (With Observability)**
**Location**: `/root/projects/learn-harness-engineering/projects/project-05/starter/AGENTS.md`

```markdown
# AGENTS.md

This repository is designed for long-running coding-agent work. The goal is not
to maximize raw code output. The goal is to leave the repo in a state where the
next session can continue without guessing.

## Startup Workflow

Before writing code:

1. Confirm the working directory with `pwd`.
2. Read `claude-progress.md` for the latest verified state and next step.
3. Read `feature_list.json` and choose the highest-priority unfinished feature.
4. Review recent commits with `git log --oneline -5`.
5. Run `./init.sh`.
6. Run the required smoke or end-to-end verification before starting new work.

If baseline verification is already failing, fix that first. Do not stack new
feature work on top of a broken starting state.

## Working Rules

- Work on one feature at a time.
- Do not mark a feature complete just because code was added.
- Keep changes within the selected feature scope unless a blocker forces a
  narrow supporting fix.
- Do not silently change verification rules during implementation.
- Prefer durable repo artifacts over chat summaries.

## Runtime Observability

All services use structured logging via `src/services/logger.ts`. Log output is
JSON-formatted with timestamp, level, service name, and message. Log levels:
DEBUG, INFO, WARN, ERROR.

When debugging, check logs for:
- Service initialization events at startup
- IPC channel invocations and their parameters
- Indexing chunk counts and content lengths
- Q&A confidence scores and citation counts

## Architecture Constraints

The following layer boundaries are enforced by `scripts/check-architecture.sh`:

- **Renderer** must not import `fs`, `path`, or any Node.js core modules.
- **Services** must not import Electron IPC or renderer-specific modules.
- **Preload** must only expose the typed API via contextBridge.

Run `bash scripts/check-architecture.sh` before committing.

## Required Artifacts

- `feature_list.json`: source of truth for feature state
- `claude-progress.md`: session log and current verified status
- `init.sh`: standard startup and verification path
- `session-handoff.md`: optional compact handoff for larger sessions
- `clean-state-checklist.md`: pre-commit repository health check

## Definition Of Done

A feature is done only when all of the following are true:

- the target behavior is implemented
- the required verification actually ran
- evidence is recorded in `feature_list.json` or `claude-progress.md`
- the repository remains restartable from the standard startup path
- `scripts/check-architecture.sh` passes with no violations

## End Of Session

Before ending a session:

1. Update `claude-progress.md`.
2. Update `feature_list.json`.
3. Record any unresolved risk or blocker.
4. Run `bash scripts/check-architecture.sh`.
5. Commit with a descriptive message once the work is in a safe state.
6. Leave the repo clean enough for the next session to run `./init.sh`
   immediately.
```

#### **Project 05 Starter: clean-state-checklist.md (Extended Example)**
**Location**: `/root/projects/learn-harness-engineering/projects/project-05/starter/clean-state-checklist.md`

```markdown
# Clean State Checklist

Run this checklist before committing and at the end of each session.

## Build

- [ ] `npm run check` passes with no type errors
- [ ] `npm run build` completes successfully

## Architecture

- [ ] `bash scripts/check-architecture.sh` passes with no violations
- [ ] No `fs` or `path` imports in renderer code
- [ ] No Electron IPC in service code
- [ ] No React imports in services or main process

## Runtime

- [ ] Application starts without errors (`npm run dev`)
- [ ] Structured log output appears in console at startup
- [ ] Document import works (check logs for IMPORT_DOCUMENT event)
- [ ] Indexing works for documents of all sizes
- [ ] Q&A returns answers with citations (check logs for ASK_QUESTION event)

## Data Integrity

- [ ] No empty chunks in indexed documents (verify with GET_CHUNKS)
- [ ] Q&A history persists across restarts
- [ ] Document metadata is consistent with actual files

## Repository

- [ ] No unintended files in git status
- [ ] No sensitive data (.env, credentials) staged
- [ ] `claude-progress.md` updated with current state
- [ ] `feature_list.json` reflects actual feature status
```

---

### **PART 3: ADVANCED TEMPLATES - OpenAI Advanced Pack**

#### **OpenAI Advanced Template: AGENTS.md**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/openai-advanced/repo-template/AGENTS.md`

```markdown
# AGENTS.md

This repository is optimized for long-running coding-agent work. Keep this file
short. Use it as the routing layer into the system-of-record docs, not as a
giant instruction dump.

## Startup Workflow

Before changing code:

1. Confirm the repo root with `pwd`.
2. Read `ARCHITECTURE.md` for the current system map and hard dependency rules.
3. Read `docs/QUALITY_SCORE.md` to see which domains or layers are weakest.
4. Read `docs/PLANS.md`, then open the active plan you are working from.
5. Read the relevant product spec in `docs/product-specs/`.
6. Run the standard bootstrap and verification path for this repo.
7. If baseline verification is failing, repair the baseline before adding scope.

## Routing Map

- `ARCHITECTURE.md`: domain map, layer model, dependency rules
- `docs/design-docs/index.md`: design decisions and core beliefs
- `docs/product-specs/index.md`: current product behaviors and acceptance targets
- `docs/PLANS.md`: plan lifecycle and execution-plan policy
- `docs/QUALITY_SCORE.md`: product-domain and layer health
- `docs/RELIABILITY.md`: runtime signals, benchmarks, and restart expectations
- `docs/SECURITY.md`: secrets, sandbox, data, and external-action rules
- `docs/FRONTEND.md`: UI constraints, design system rules, accessibility checks

## Working Contract

- Work from one bounded plan or feature slice at a time.
- Do not mark work done from code inspection alone; runnable evidence is
  required.
- If you change behavior, update the matching product, plan, or reliability
  docs in the same session.
- If you see repeated review feedback, promote it into a mechanical rule, check,
  or linter instead of re-explaining it in chat.
- Keep generated material in `docs/generated/` and source references in
  `docs/references/`.
- Prefer adding small, current docs over growing this file.

## Definition Of Done

A change is done only when all of the following are true:

- target behavior is implemented
- required verification actually ran
- evidence is linked from the relevant plan or quality document
- affected docs remain current
- the repository can restart cleanly from the standard startup path

## End Of Session

Before ending a session:

1. Update the active execution plan.
2. Update `docs/QUALITY_SCORE.md` if any domain or layer meaningfully changed.
3. Record new debt in `docs/exec-plans/tech-debt-tracker.md` if you deferred it.
4. Move finished plans to `docs/exec-plans/completed/` when appropriate.
5. Leave the repo in a restartable state with a clear next action.
```

#### **OpenAI Advanced Template: ARCHITECTURE.md**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/openai-advanced/repo-template/ARCHITECTURE.md`

```markdown
# ARCHITECTURE.md

This file is the top-level map of the system. It should stay concise and point
to deeper documents when needed.

## System Shape

- Product: `[replace with product name]`
- Primary user workflow: `[replace with main workflow]`
- Runtime surfaces: `[desktop / web / cli / services / workers]`
- Source of truth for product behavior: `docs/product-specs/`

## Domain Map

| Domain | Purpose | Primary Entry Points | Related Spec |
|--------|---------|----------------------|--------------|
| `[domain-a]` | `[what it owns]` | `[modules / routes / commands]` | `[spec path]` |
| `[domain-b]` | `[what it owns]` | `[modules / routes / commands]` | `[spec path]` |

## Layer Model

Use a fixed directional model so agents do not invent ad hoc architecture:

`Types -> Config -> Repo -> Service -> Runtime -> UI`

Cross-cutting concerns should enter through explicit provider or adapter
boundaries instead of reaching across layers directly.

## Hard Dependency Rules

- Lower layers must not depend on higher layers.
- UI must not bypass runtime or service contracts.
- Data access must enter through repositories or equivalent adapters.
- Shared utilities must remain generic and must not accumulate domain logic.
- New dependencies should be justified in the matching plan or design doc.

## Cross-Cutting Interfaces

| Concern | Approved Boundary | Notes |
|--------|-------------------|-------|
| Logging and tracing | `[provider / utility path]` | `[structured only, no ad hoc console use]` |
| Auth | `[provider path]` | `[token/session rules]` |
| External APIs | `[client or provider path]` | `[rate limit / retry guidance]` |
| Feature flags | `[flag boundary]` | `[ownership]` |

## Current Hot Spots

- `[area that is hardest for agents to change safely]`
- `[area with weak boundaries or fragile tests]`

## Change Checklist

When you touch architecture-relevant code:

1. Update this file if the domain map or allowed boundaries changed.
2. Update the related design doc in `docs/design-docs/` if the reasoning changed.
3. Add or update an executable check if the rule should be enforced mechanically.
```

---

### **PART 4: REFERENCE DOCUMENTS - Harness Engineering Best Practices**

#### **Initializer Agent Playbook**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/reference/initializer-agent-playbook.md`

```markdown
# Initializer Agent Playbook

Use this playbook for the first serious session in a repository, before
incremental feature work begins.

## Goal

Create a stable operating surface so later sessions can implement behavior
without re-deriving startup commands, current status, or task boundaries.

## Required Outputs

The initializer should leave behind at least these artifacts:

- a root instruction file such as `AGENTS.md` or `CLAUDE.md`
- a machine-readable feature surface such as `feature_list.json`
- a durable progress artifact such as `claude-progress.md`
- a standard startup helper such as `init.sh`
- an initial safe commit that captures the baseline scaffold

## Checklist

1. Define the standard startup path.
2. Define the standard verification path.
3. Create the progress log and record the starting state.
4. Decompose the work into explicit features with statuses.
5. Create the first clean baseline commit.

## Success Test

A fresh session with no prior chat context should be able to answer:

- what this repository does
- how to start it
- how to verify it
- what is unfinished
- what the next best step is
```

#### **Coding Agent Startup Flow**
**Location**: `/root/projects/learn-harness-engineering/docs/en/resources/reference/coding-agent-startup-flow.md`

```markdown
# Coding Agent Startup Flow

Use this at the beginning of every session after initialization is complete.

## Fixed Startup Template

1. Run `pwd` and confirm the repository root.
2. Read `claude-progress.md`.
3. Read `feature_list.json`.
4. Review recent commits with `git log --oneline -5`.
5. Run `./init.sh`.
6. Run a baseline smoke or end-to-end path.
7. If the baseline is broken, fix that first.
8. Select the highest-priority unfinished feature.
9. Work only on that feature until it is verified or explicitly blocked.

## Why This Order Matters

- `pwd` prevents accidental work in the wrong directory.
- progress and feature files recover durable state before new edits begin.
- recent commits explain what changed most recently.
- `init.sh` standardizes startup instead of relying on memory.
- baseline verification catches broken starting states before new work hides
  them.

## End-Of-Session Mirror

The same session should end by:

1. recording progress
2. updating feature state
3. writing a handoff if needed
4. committing safe work
5. leaving a clean restart path
```

---

### **PART 5: ARCHITECTURE DOCUMENTATION EXAMPLE**

#### **Project 02: Architecture Documentation**
**Location**: `/root/projects/learn-harness-engineering/projects/project-02/starter/docs/ARCHITECTURE.md`

```markdown
# Architecture -- Knowledge Base Electron App

## System Overview

The Knowledge Base is an Electron desktop application built with TypeScript and React. It provides document import, text indexing with chunking, and grounded question answering with citations.

## Layer Diagram

```
+-----------------------------------------------------------+
|                     Renderer (React)                       |
|  App.tsx -> DocumentList, DocumentDetail, QuestionPanel,  |
|             StatusBar, ImportPanel                         |
+-----------------------------------------------------------+
         |  window.knowledgeBase.* (typed IPC bridge)
+-----------------------------------------------------------+
|                     Preload Script                         |
|  contextBridge.exposeInMainWorld -> documents, indexing, qa|
+-----------------------------------------------------------+
         |  ipcRenderer.invoke(IPC_CHANNELS.*)
+-----------------------------------------------------------+
|                     Main Process                           |
|  main.ts -> createWindow(), initializeServices()          |
|  ipc-handlers.ts -> registerIpcHandlers()                  |
+-----------------------------------------------------------+
         |  Service method calls
+-----------------------------------------------------------+
|                     Services Layer                         |
|  DocumentService | IndexingService | QaService             |
|  PersistenceService (filesystem I/O)                       |
+-----------------------------------------------------------+
```

## Electron Layers

### Main Process (`src/main/`)

The main process is the Node.js process that manages the application lifecycle. Responsibilities:

- **Window management**: Creates `BrowserWindow` instances with secure web preferences (`contextIsolation: true`, `nodeIntegration: false`).
- **IPC registration**: Maps IPC channel names to service methods via `registerIpcHandlers()`.
- **Service initialization**: Constructs `PersistenceService`, `DocumentService`, `IndexingService`, and `QaService` with dependency injection.

**Key invariant**: The main process never imports React or renderer code.

### Preload (`src/preload/`)

The preload script runs in the renderer context before any page scripts load. It uses Electron's `contextBridge` to expose a limited, typed API:

```typescript
window.knowledgeBase = {
  documents: { list, import, get, delete },
  indexing:   { start, status, chunks },
  qa:         { ask, history },
}
```

**Key invariant**: The preload bridge is the only communication channel between renderer and main. No Node.js modules are accessible from the renderer.

### Renderer (`src/renderer/`)

The renderer is a React 18 application bundled by Vite. Components:

- `App.tsx` -- Root layout with header, sidebar, main panel, and status bar.
- `DocumentList` -- Sidebar listing of imported documents.
- `DocumentDetail` -- Shows document metadata, chunks, and indexing controls.
- `ImportPanel` -- File input for importing .txt and .md documents.
- `QuestionPanel` -- Text input for asking questions.
- `StatusBar` -- Shows index status and document count.

**Key invariant**: Renderer code never imports `fs`, `path`, `electron`, or any Node.js module.

### Services (`src/services/`)

Business logic classes running in the main process:

- `PersistenceService` -- Low-level JSON/text file I/O with atomic writes.
- `DocumentService` -- Document CRUD operations (import, list, get, update, delete).
- `IndexingService` -- Paragraph-aware chunking (~500 chars per chunk) and index management.
- `QaService` -- Mock question answering with keyword-based retrieval and citation generation.

**Key invariant**: Services may import shared types but never renderer code.

## Data Flow

1. User interacts with a React component (e.g., clicks "Ask").
2. Component calls `window.knowledgeBase.qa.ask(question)`.
3. Preload bridge invokes `ipcRenderer.invoke('qa:ask', question)`.
4. Main process IPC handler delegates to `QaService.ask()`.
5. QaService retrieves chunks, scores by keyword overlap, generates answer.
6. Response flows back through IPC to the renderer.
7. React component updates state and re-renders.

## Build Pipeline

1. `tsc -p tsconfig.node.json` compiles main, preload, shared, and services to `dist/`.
2. `vite build` bundles the renderer React app to `dist/renderer/`.
3. Electron loads `dist/main/main.js` as the entry point.

## Data Storage

All user data is stored under `app.getPath('userData')/knowledge-base-data/`:

```
knowledge-base-data/
  documents-meta.json     # Document metadata array
  content/
    <doc-id>.txt          # Extracted text content per document
  chunks/
    <doc-id>.json         # Chunk array per document
  index/
    index-meta.json       # Mapping of document IDs to chunk IDs
  qa-history.json         # Q&A interaction log
```
```

---

### **SUMMARY OF KEY PATTERNS**

**The Five Essential Harness Artifacts**:

1. **CLAUDE.md** or **AGENTS.md** — Root instruction file with startup workflow and completion rules
2. **feature_list.json** — Machine-readable feature state with verification checklist
3. **claude-progress.md** — Session log documenting state, decisions, and next steps
4. **init.sh** — Standard startup automation (install → verify → run)
5. **session-handoff.md** — Optional but recommended for complex projects

**Harness Subsystems** (from the course):

1. **Instructions** — AGENTS.md, CLAUDE.md, ARCHITECTURE.md
2. **Tools** — Shell commands, npm scripts, build pipelines
3. **Environment** — Directory structure, type definitions, shared constants
4. **State** — feature_list.json, claude-progress.md, git history
5. **Feedback** — Verification commands, logs, test output

**Critical Rules**:

- **One feature at a time** — Never stack new work on broken baselines
- **Verification is mandatory** — No feature complete without runnable evidence
- **Repository is system of record** — Never rely on chat history alone
- **Session continuity** — Every session must leave clear handoff for the next
- **Clean state** — Before committing, verify startup path still works

All files are in absolute paths starting from `/root/projects/learn-harness-engineering/`

Prompt:
I need to explore the template and resource files in /root/projects/learn-harness-engineering that relate to harness engineering templates and best practices.

Please do a VERY THOROUGH exploration:

1. Look at docs/resources/en/ and docs/resources/zh/ for any template files, especially:
   - CLAUDE.md templates
   - AGENTS.md templates
   - Any harness setup guides
   - Any reference documents about harness engineering
2. Look at the actual harness files in project directories:
   - projects/project-01/ through project-06/ - look at starter/ directories for CLAUDE.md, AGENTS.md, feature_list.json, init.sh, etc.
   - Read at least 2-3 of these completely to understand the pattern
3. Look at projects/shared/ for the base harness setup

I specifically want to see:
- Complete examples of CLAUDE.md files used in projects
- Complete examples of AGENTS.md files
- feature_list.json format and content
- init.sh scripts
- Any other harness artifacts

Report back with FULL file contents of the most representative examples.


Perfect! I have comprehensive information now. Let me compile a detailed report for the user:

## Comprehensive Harness Engineering Best Practices Report

Based on my thorough exploration of the learn-harness-engineering project, here are the key findings:

---

## **KEY PRINCIPLES OF HARNESS ENGINEERING**

The course teaches that **model capability and execution reliability are fundamentally different things**. A strong model in a terrible harness still fails. The "harness" is everything outside the model—instructions, tools, environment, state management, and verification feedback.

### Core Principle Stack

The five subsystems of a harness (from Lecture 02):

1. **Instructions** - Tell the agent what to do, in what order, and what to read
2. **Tools** - Agent access to environments and commands
3. **Environment** - Self-describing project state, dependencies, versions
4. **State** - Persistent progress tracking across sessions
5. **Feedback** - Verification commands and runtime signals

The weakest subsystem determines overall effectiveness. Lecture 02 shows real data: a TypeScript/React frontend went from 20% success rate (minimal harness) to 80-100% (full five-tuple harness) by systematically improving each subsystem.

---

## **WHAT FILES MAKE UP A GOOD HARNESS**

A complete harness consists of these artifacts (found in `/root/projects/learn-harness-engineering/docs/en/resources/templates/` and demonstrated in project solutions):

### **Core Required Files** (4 files minimum)

1. **`AGENTS.md`** (or `CLAUDE.md` for Claude Code) — The routing/entry file
   - **Path example**: `/root/projects/learn-harness-engineering/projects/project-01/solution/AGENTS.md`
   - **Purpose**: First thing the agent reads; defines startup workflow, working rules, definition of done
   - **Content**:
     - Startup checklist (read progress, read features, run init.sh)
     - Working rules (one feature at a time, no overreach)
     - Hard constraints (15 or fewer global rules, at top/bottom to avoid "lost in the middle" effect)
     - Required artifacts list
     - Definition of Done (completion criteria: code written + verification ran + evidence recorded)
   - **Size**: 50-200 lines (template is 56 lines)
   - **Key rule**: Don't stuff everything here. Use it as a router pointing to topic docs.

2. **`init.sh`** — Bootstrap script
   - **Path example**: `/root/projects/learn-harness-engineering/projects/project-01/solution/init.sh`
   - **Purpose**: Standardized startup path; agents run this at session start
   - **Content**:
     - `npm install` (or equivalent dependency installation)
     - `npm run check` (type checking)
     - `npm run build` (build verification)
   - **Why**: Ensures baseline is clean before agents start work; includes verification steps upfront

3. **`feature_list.json`** — Machine-readable task state tracker
   - **Path example**: `/root/projects/learn-harness-engineering/projects/project-01/solution/feature_list.json`
   - **Purpose**: Single source of truth for project state; essential for scope control
   - **Structure**:
     ```json
     {
       "project": "project-name",
       "features": [
         {
           "id": "F01",
           "behavior": "User can do X",
           "verification": "curl -X POST ... | jq .status == 201",
           "status": "passing",  // not_started, in_progress, blocked, passing
           "evidence": "commit abc123"
         }
       ]
     }
     ```
   - **Rules**:
     - Each feature has a triple: (behavior, verification command, status)
     - Only ONE feature can be `in_progress` at a time (WIP=1)
     - Status moves to `passing` only when verification actually succeeds
     - Pass-state gating: harness controls transitions, agent can't force it

4. **`claude-progress.md`** — Session continuity log
   - **Path example**: `/root/projects/learn-harness-engineering/projects/project-01/solution/claude-progress.md`
   - **Purpose**: Cross-session continuity artifact; every new session reads this first
   - **Content**:
     - Current verified state (commit hash, test status)
     - Completed features (with evidence)
     - In-progress features (with blockers)
     - Known issues
     - Next steps
   - **Timing**: Updated before every session ends

### **Advanced Optional Files** (add as project grows)

5. **`session-handoff.md`** — Compact handoff for complex sessions
   - **Path example**: `/root/projects/learn-harness-engineering/projects/project-03/solution/session-handoff.md`
   - **Content**: What was accomplished, what remains, decisions made, files modified, blockers, next steps
   - **When to use**: Sessions longer than 45 minutes or complex multi-feature work

6. **`clean-state-checklist.md`** — Pre-commit validation
   - **Path example**: `/root/projects/learn-harness-engineering/projects/project-04/solution/clean-state-checklist.md`
   - **Purpose**: Verify repo health before ending session
   - **Checks**:
     - [ ] Build passes
     - [ ] Tests pass
     - [ ] No debug code (console.log, debugger)
     - [ ] No untracked files
     - [ ] Progress files updated
     - [ ] Architecture constraints met

7. **Architecture docs** (e.g., `docs/ARCHITECTURE.md`) — Layer boundaries
   - Describes module responsibilities and constraints
   - Placed next to code it describes (not in a giant central doc)

8. **`evaluator-rubric.md`** — Quality scorecard
   - Grades work across 6 dimensions: correctness, verification, scope discipline, reliability, maintainability, handoff readiness
   - Used to evaluate agent output quality systematically

---

## **KEY PATTERNS AND BEST PRACTICES**

### **Pattern 1: Progressive Disclosure (Lecture 04)**

**Problem**: Giant 600-line AGENTS.md causes "lost in the middle" effect (critical info at line 300 is ignored by models).

**Solution**: Three-layer instruction structure:
- **Layer 1 (Routing file)**: AGENTS.md, 50-200 lines, only overview + hard constraints + links
- **Layer 2 (Topic documents)**: `docs/api-patterns.md`, `docs/database-rules.md`, loaded on demand
- **Layer 3 (Inline)**: Comments in code where constraints apply

**Real example from Lecture 04**: SaaS team reduced AGENTS.md from 600 to 80 lines by splitting into topic docs. Result: success rate 45% → 72%, security compliance 60% → 95%.

### **Pattern 2: Work-in-Progress Limit (Lecture 07)**

**Problem**: Agents activate 5 features at once, finish 0 completely (overreach + under-finish).

**Solution**: Enforce WIP=1 in AGENTS.md:
```
## Work Rules
- Work on one feature at a time
- Only start next feature after current passes verification
- Don't refactor feature B while implementing feature A
```

**Data from Lecture 07**:
- Unconstrained: agent produces 800 lines across 12 files, 20% end-to-end pass rate (only 1 of 5 features work)
- WIP=1: agent produces 200 lines, 100% pass rate for completed features, 7 of 8 total features complete

**Key metric**: Verified Completion Rate (VCR) = verified tasks / activated tasks. Keep this at 1.0.

### **Pattern 3: Feature List as Harness Primitive (Lecture 08)**

**Problem**: Unstructured progress notes ("mostly done cart, still need payments") lead to duplicate work and missed requirements.

**Solution**: Feature list is not a document, it's a data structure the harness executes against:
- Scheduler reads states, picks next `not_started` feature
- Verifier executes verification commands, controls state transitions
- Handoff reporter auto-generates summaries
- Progress tracker provides health metrics

**Granularity rule**: Scope each feature to "completable in one session" (~1 hour of focused work).

### **Pattern 4: ACID State Management (Lecture 03)**

Apply database transaction principles to agent state:
- **Atomicity**: Each logical operation gets one git commit; `git stash` to rollback
- **Consistency**: Define "consistent state" predicates (all tests pass, lint clean); verify before committing
- **Isolation**: Concurrent agents use separate branches or feature files
- **Durability**: Critical knowledge in git-tracked files (not just session memory)

### **Pattern 5: Three-Layer Verification (Lecture 09)**

Don't accept unit tests as evidence of completion:
- **Layer 1**: Unit tests (fastest, most blind spots)
- **Layer 2**: Integration tests (catches component boundary issues)
- **Layer 3**: End-to-end tests (catches system-level defects)

**Required**: All three must pass before marking feature as "passing".

### **Pattern 6: Multi-Artifact Continuity (Lecture 05)**

Long tasks spanning sessions require:
- **Progress file**: Current state, tests passing, next steps
- **Decision log**: Why was option B chosen over A?
- **Git commits**: Checkpoint statements
- **Init workflow**: Written in AGENTS.md

**Real data from Lecture 05**:
- Without artifacts: 7 of 12 features complete, rebuild cost 15 min per session
- With artifacts: 12 of 12 features complete, rebuild cost 3 min per session

### **Pattern 7: Dedicated Initialization Phase (Lecture 06)**

Don't mix initialization with feature implementation:

**Initialization output** (no business code):
1. Runnable environment
2. Verifiable test framework (≥1 passing test proves it works)
3. Bootstrap contract document
4. Task breakdown file
5. Git checkpoint

**Result**: Next session spends <3 min understanding state instead of 20 min re-exploring.

### **Pattern 8: Observable Runtime (Lecture 11)**

Without runtime observability, agents make blind decisions:
- Structured logging (JSON format with timestamp, level, service name)
- Process tracing (which paths executed, what data flowed)
- Health checks (startup events, IPC invocations, critical path execution)

**Example from project-04**: `src/services/logger.ts` provides structured logging; AGENTS.md tells agents to check logs for service init, IPC calls, indexing chunk counts.

### **Pattern 9: Clean State Exits (Lecture 12)**

Every session must end in a clean state:
```
Before session end:
1. Update claude-progress.md
2. Update feature_list.json
3. Run bash scripts/check-architecture.sh
4. Commit all completed work
5. Verify: `npm run build && npm test` both pass
```

**Metric that matters**: Can the next session run `./init.sh` immediately and continue? Yes = clean state.

**Data from Lecture 12**: Projects with cleanup strategy: build pass rate 97% in week 12. Without: 68%.

---

## **WHAT A COMPLETE HARNESS LOOKS LIKE IN PRACTICE**

### **Project 01 Baseline** (minimal harness)
- **Path**: `/root/projects/learn-harness-engineering/projects/project-01/solution/`
- **Contains**:
  - AGENTS.md (startup rules, layer boundaries, definition of done)
  - CLAUDE.md (quick reference for Claude Code)
  - feature_list.json (4 features, all passing)
  - init.sh (verify dependencies, type-check, build)
  - claude-progress.md (session log with decisions and next steps)
  - docs/ARCHITECTURE.md (4 Electron layers and their contracts)
  - docs/PRODUCT.md (feature requirements)
- **Verification**: npm run check (type-check), npm run dev (launch), npm test (tests)
- **Result**: Baseline agent success rate ~60-70%

### **Project 03 Multi-Session Example** (intermediate harness)
- **Path**: `/root/projects/learn-harness-engineering/projects/project-03/solution/`
- **Adds over P01**:
  - session-handoff.md (detailed handoff with decisions and files modified)
  - clean-state-checklist.md (20-item health check)
  - **feature_list.json**: 11 features with detailed evidence
    - Metadata Extraction — "extractMetadata() analyzes content, DocumentDetail displays metadata"
    - Document Chunking — "chunks stored as JSON in chunks/<docId>.json with charCount/wordCount"
    - Indexing Status UI — "color-coded status indicator, indexed count, total chunks"
    - Grounded Q&A — "keyword retrieval returns top 2 chunks as citations with confidence scoring"
  - **Architecture enforcement**: scripts/check-architecture.sh validates layer boundaries
- **Key decision documented**: "Metadata extracted at import time (not lazily) to ensure availability"
- **Result**: Agent success rate ~80-90%, rebuild time <3 min

### **Project 04 Full Harness** (advanced harness)
- **Path**: `/root/projects/learn-harness-engineering/projects/project-04/solution/`
- **Key additions**:
  - AGENTS.md explicitly covers: startup workflow, working rules, runtime observability, architecture constraints, required artifacts, definition of done, end-of-session checklist
  - Structured logging via `src/services/logger.ts` with DEBUG/INFO/WARN/ERROR levels
  - Verification script (`scripts/check-architecture.sh`) to enforce no fs/path in renderer, no Electron in services
  - clean-state-checklist.md with runtime verification section: "Structured log output appears at startup", "Document import works (check logs for IMPORT_DOCUMENT event)"
  - Feature list tracks: window launch, document list, question panel, data directory, document import, detail view, persistence, chunking, metadata, indexing UI, Q&A, history
- **Architecture constraints enforced at commit time**: No "pushing broken code and fixing later"
- **Result**: Agent success rate ~90%+, multi-session reliability very high

---

## **TEMPLATES AND REFERENCE ARTIFACTS**

All templates available at: `/root/projects/learn-harness-engineering/docs/en/resources/templates/`

1. **AGENTS.md template** (56 lines) — Startup workflow, working rules, definition of done
2. **init.sh template** — Standardized install, verify, build steps
3. **claude-progress.md template** — Current state, session record structure
4. **feature_list.json template** — Feature schema with behavior, verification, status triple
5. **session-handoff.md template** — Accomplishments, decisions, blockers, next steps
6. **clean-state-checklist.md template** — Build, tests, architecture, runtime, data, repo checks
7. **evaluator-rubric.md template** — 6-dimension quality scorecard
8. **quality-document.md template** — Codebase health grades per domain and layer

---

## **THE 12-LECTURE CURRICULUM STRUCTURE**

The course is organized around **5 failure modes that harnesses prevent**:

1. **Lecture 01**: Why models fail (5 defense layers: task spec, context, environment, verification, state)
2. **Lectures 02-04**: Build the five-subsystem harness (instructions split across files)
3. **Lectures 05-06**: Maintain continuity (state persistence, dedicated initialization)
4. **Lectures 07-08**: Control scope (WIP=1, feature lists as primitives)
5. **Lectures 09-10**: Verify completion (three-layer verification, end-to-end tests)
6. **Lectures 11-12**: Observe and clean (runtime observability, clean state exits)

---

## **KEY METRICS THAT MATTER**

- **Verified Completion Rate** (VCR) = features passing verification / features activated
- **Rebuild cost** = minutes needed for new session to reach working state (target: <3 min)
- **Feature completion rate** = features passing / total features (compare with/without harness)
- **Verification gap** = (agent says done but actually broken) / total tasks
- **Knowledge visibility gap** = (critical info outside repo) / (total critical info)

---

## **CRITICAL INSIGHTS FROM THE COURSE**

1. **Same model, different harnesses = order-of-magnitude difference**: Anthropic's experiment shows Opus 4.5 with bare prompt = $9, 20 min, broken output; same model with full harness = $200, 6 hours, working application.

2. **"Add a rule" is a slippery slope**: Each time something fails, agents naturally want to add a rule to AGENTS.md. But this bloats the file and introduces the "lost in the middle" effect. Solution: split into topic documents.

3. **Feature lists are not planning tools**: They're data structures the harness executes against. The agent can't change feature states; the harness does, based on verification results.

4. **Unit tests passing ≠ task complete**: Component boundary defects are invisible to unit tests. Only integration + end-to-end tests catch them.

5. **Initialization is its own phase**: Mixing initialization with feature work leads to incomplete infrastructure. Spend one session on init (no business code), then subsequent sessions fly.

6. **Session handoff is not optional**: Without progress files + decision logs, every new session re-explores the project. Handoff artifacts reduce startup time from 15 min to 3 min.

7. **Clean state is a completion requirement**: If the repo builds broken or tests fail, the session isn't done. This forces agents to leave clean checkpoints.

---

## **FILE PATH SUMMARY**

**Core lectures** (understand these in order):
- `/root/projects/learn-harness-engineering/docs/en/lectures/lecture-01-why-capable-agents-still-fail/index.md`
- `/root/projects/learn-harness-engineering/docs/en/lectures/lecture-02-what-a-harness-actually-is/index.md`
- `/root/projects/learn-harness-engineering/docs/en/lectures/lecture-07-why-agents-overreach-and-under-finish/index.md`
- `/root/projects/learn-harness-engineering/docs/en/lectures/lecture-08-why-feature-lists-are-harness-primitives/index.md`

**Complete example harnesses** (working implementations):
- Project 01 (minimal): `/root/projects/learn-harness-engineering/projects/project-01/solution/`
- Project 03 (intermediate): `/root/projects/learn-harness-engineering/projects/project-03/solution/`
- Project 04 (full): `/root/projects/learn-harness-engineering/projects/project-04/solution/`

**Templates** (copy-paste starting points):
- `/root/projects/learn-harness-engineering/docs/en/resources/templates/`

**VitePress config** (curriculum overview):
- `/root/projects/learn-harness-engineering/docs/.vitepress/config.mts` (12 lectures, 6 projects, all organized)

Prompt:
I need to understand the harness engineering best practices taught in the learn-harness-engineering project at /root/projects/learn-harness-engineering.

Please do a VERY THOROUGH exploration:

1. Read the lecture index files to understand what topics are covered (look at docs/lectures/ directory structure and content)
2. Read the project descriptions in docs/projects/ to understand what hands-on projects teach
3. Look at example AGENTS.md, CLAUDE.md, and other harness files in the projects/ directory (especially in projects/shared/ and any project starter/solution directories)
4. Look at docs/resources/ for templates and references about harness engineering
5. Read the VitePress config to understand the full curriculum structure

I want to know:
- What are the key principles of harness engineering taught in this course?
- What files/artifacts make up a good harness? (AGENTS.md, CLAUDE.md, feature_list.json, init.sh, etc.)
- What patterns and best practices are recommended?
- What does a complete harness look like in practice?

Report back with detailed findings including file paths and key content snippets.


Excellent! Now I have a comprehensive view. Let me compile all this into a detailed report for the user.

## Detailed Harness Exploration Report: /root/projects/meeting

I've completed a thorough exploration of the meeting project's harness setup. Here's what I found:

---

### **1. CLAUDE.md Content**

The CLAUDE.md file outlines the project's guidelines including:
- **Core Workflow**: TDD-strict approach, spec-first, plain English explanations
- **Python Standards**: Type hints mandatory, Pydantic for data validation, pathlib for file handling
- **Human-in-the-Loop Protocol**: Requires self-explanation, structural checks, risk assessment, and verification plans after significant code changes
- **References Chinese-language superpowers** for specific task types (brainstorming, code review, debugging)
- **References ECC (Everything Claude Code)** skills for technical reviews in Go, Python, security, databases, etc.

---

### **2. .claude/ Directory Structure**

The project HAS a `.claude` directory with:
- **`settings.local.json`** - Permission rules for file access
  - Primarily defined for macOS paths (`/Users/lili/`), suggesting this was developed on a Mac
  - Contains specific bash command allowlists for find, grep, git, Python, and other tools
  - Includes SSH/rsync/SCP permissions

- **`skills/meeting/SKILL.md`** - A detailed skill definition for running multi-agent meetings
  - Metadata: `name: meeting`, `description: "Multi-agent debate meeting"`, `allowed-tools: [Read, Glob, Grep, Bash, Write, AskUserQuestion, Agent]`
  - 180 lines of structured guidance for using the meeting skill
  - Includes clarification prompts, persona categories, meeting structure, formatting guidelines
  - Persona categories: Strategic thinkers (Munger, Bezos, Grove), Domain experts (architect, devops), Industry legends, and specialized reviewers
  - Recommends 3-5 participants per meeting

---

### **3. Agent Configurations**

The project contains **30+ agent JSON configs** in `/root/projects/meeting/agents/`:

**Core Agent Types:**
- **Basic roles** (3): `architect.json`, `business_analyst.json`, `devops.json` - Simple role + system_prompt
- **ECC specialists** (9): `ecc_tdd_guide.json`, `ecc_python_reviewer.json`, `ecc_security_reviewer.json`, etc.
- **GStack personas** (15+): `gstack_munger.json`, `gstack_bezos.json`, `gstack_grove.json`, `gstack_horowitz.json`, `gstack_pg.json`, etc.
- **Strategic integrator**: `real_powell.json` - The "cross-dimensional integrator" role (highest level strategic synthesis)
- **Example**: `example_architect.json`, `steve_jobs.json`

**Sample agent config structure:**
```json
{
  "name": "architect",
  "role": "Senior Software Architect",
  "system_prompt": "你是一位拥有15年经验的资深软件架构师..."
}
```

**Standout Agent - real_powell.json:**
- Role: "🧭 战略整合者 Powell (The Strategic Integrator)"
- 2000+ character system prompt focusing on:
  - Cross-dimensional integration (tech + business + org + strategy)
  - Problem decomposition, assumption-checking, alternative evaluation
  - Cost/benefit analysis and risk assessment
  - Strategic vs. tactical victory distinction
  - Rejection of corporate speak and false balance
  - Serves as "final synthesizer" speaking last

---

### **4. Architecture & Source Code (3051 lines total)**

**Core Modules in `/src/`:**

1. **`models.py`** - Pydantic data models:
   - `AgentConfig`: name, role, system_prompt, input/output_schema
   - `ScratchpadEntry`: agent_name, content, timestamp
   - `MeetingState`: topic, context, context_summary, scratchpad, current_round, max_rounds
   - `PMDecision`: analysis, next_action (CALL_AGENT|FINISH), target_agent, prompt_for_agent, final_report
   - `MeetingResult`: topic, participants, transcript, final_report, started_at, finished_at

2. **`meeting.py`** - Event loop orchestration:
   - `_run_meeting_loop()`: Main state machine (while current_round < max_rounds)
   - `run_meeting()`: Full meeting execution
   - `run_meeting_interactive()`: Human-in-the-loop mode with user feedback
   - `save_report()`, `save_transcript()`: Markdown output with timestamp + slugified topic
   - Colored terminal output for different roles (PM=blue, agents=green, system=yellow, human=magenta)

3. **`pm.py`** - PM Agent router:
   - `build_pm_system_prompt()`: Dynamically generates PM's instructions with available agents listed
   - `run_pm()`: Calls LLM with state, validates JSON response, handles retries (up to 5)
   - Forces PM to output structured JSON decisions

4. **`agent.py`** - Stateless agent executor:
   - `run_agent()`: Calls target agent with only their specific prompt + scratchpad summary
   - `format_scratchpad_summary()`: Formats meeting transcript for agent context

5. **`context_manager.py`** (380+ lines) - Intelligent whiteboard compression:
   - `estimate_tokens()`: Heuristic token estimation (Chinese ~1.5 chars/token, English ~4 chars/token)
   - `build_agent_context()`: Compresses old scratchpad entries, keeps recent ones in full
   - Three compression levels: full text → summarized bullets → omitted
   - Prevents "whiteboard explosion" in long meetings

6. **`llm_client.py`** - Provider abstraction:
   - `LLMClient` Protocol: `chat(system, messages) -> str`
   - `AnthropicClient`: Wraps anthropic SDK, model configurable
   - `OpenAIClient`: Wraps openai SDK
   - `create_client()`: Factory function based on `LLM_PROVIDER` env var

7. **`config_loader.py`** - JSON/YAML agent loading
8. **`agent_selector.py`** - PM auto-selection of agents by topic
9. **`scenarios.py`** - Preset meeting scenarios (tech_design, product_review, etc.)

---

### **5. Entry Points (CLI Tools)**

**`agent_builder.py`** (~110 lines):
- Generates new agent configs from natural language descriptions
- System prompt tells LLM to output JSON with `role` and `system_prompt` fields
- Saves as JSON or YAML
- Usage: `python agent_builder.py --description "..." --name NAME`

**`run_meeting.py`** (~200+ lines):
- Main CLI orchestrator
- Options:
  - `--topic` (required)
  - Agent selection: `--agents comma,separated` OR `--scenario NAME` OR `--auto-select`
  - `--context` / `--context-file` for background materials
  - `--max-rounds` (default 10)
  - `--interactive` for human-in-the-loop
  - `--context-budget` (default 6000 tokens) for whiteboard compression
  - `--no-compact` to disable compression
- Saves report + transcript to `reports/` directory

---

### **6. Testing**

**Test coverage** (12 test files, ~900+ lines):
- `test_models.py` - Pydantic model validation
- `test_agent.py` - Agent executor
- `test_pm.py` - PM router logic
- `test_meeting.py` - Event loop
- `test_context_manager.py` - Compression logic (15K+ lines = thorough!)
- `test_run_meeting_cli.py` - Integration tests
- `test_agent_builder.py`, `test_config_loader.py`, etc.

**Test infrastructure**: pytest with ~10 configured tests per module

---

### **7. Tech Stack & Dependencies**

**`requirements.txt`**:
```
pydantic>=2.0              # Data validation
anthropic>=0.40.0          # Anthropic API
openai>=1.0                # OpenAI API
pyyaml>=6.0                # YAML agent configs
python-dotenv>=1.0         # .env support
pytest>=8.0                # Testing
```

**Environment configuration** (`.env.example`):
```
LLM_PROVIDER=openai  # anthropic or openai
OPENAI_BASE_URL=...  # Optional proxy
OPENAI_API_KEY=sk-...
LLM_MODEL=gpt-4o
```

---

### **8. Project Metadata**

**Git History** (13 commits):
- Progression from data models → agent executor → PM router → meeting loop → CLI tools → agent presets → Powell integration
- Latest: "feat: add Powell (real_powell) as strategic integrator role"

**Directory Structure**:
```
/root/projects/meeting/
├── .claude/                    # Harness config
│   ├── settings.local.json
│   └── skills/meeting/SKILL.md
├── agents/                     # 30+ agent configs (JSON)
├── src/                        # 10 modules, 1680 LOC
├── tests/                      # 12 test files, ~900 LOC
├── docs/                       # USAGE.md (23K), superpowers/
├── context/                    # Sample background materials
├── reports/                    # Output: markdown reports + transcripts
├── CLAUDE.md                   # Guidelines
├── README.md                   # Quick start guide
├── prompts.md                  # Original design spec (80 lines)
├── WHO-IS-POWELL.md            # 19K character deep dive on Powell persona
├── agent_builder.py            # CLI: generate agents
├── run_meeting.py              # CLI: run meetings
├── requirements.txt
├── .env.example
└── .gitignore
```

---

### **9. What's Included (Strengths)**

✓ **Protocol-based abstraction** for LLM providers (easy to swap Anthropic ↔ OpenAI)
✓ **Structured Pydantic models** everywhere (no raw dicts)
✓ **Stateless agents** - only receive prompt + compressed whiteboard summary
✓ **State machine enforcement** - PM must decide CALL_AGENT or FINISH (no infinite loops)
✓ **Max rounds hard limit** - forced finish at round 10 (configurable)
✓ **Intelligent context compression** - 3-level truncation strategy for long meetings
✓ **Rich agent library** - 30+ pre-configured personas (including Powell integrator)
✓ **Interactive mode** - human-in-the-loop feedback mid-meeting
✓ **Complete transcript + report** - both saved to reports/ with timestamp
✓ **Full test coverage** - 12 test files with deep context_manager tests
✓ **Colored terminal output** - role-based color coding for clarity
✓ **Preset scenarios** - built-in meeting templates (tech_design, product_review, etc.)
✓ **Auto-agent selection** - PM can pick best agents for topic
✓ **SKILL.md documentation** - comprehensive usage guide (180 lines)
✓ **Type hints throughout** - full Python typing discipline

---

### **10. What's Missing (vs. Best Practices)**

✗ **No settings.json** - Only `settings.local.json` (Mac-specific, should be generic)
✗ **No AGENTS.md** - Could document all 30+ agents (what each excels at)
✗ **No feature_list.json** - Could declare available features/commands
✗ **No hooks system** - No "before/after" hooks in harness for automated workflows
✗ **No commands/ directory** - No custom slash commands configured
✗ **No top-level settings.json** - Should have one for project-wide harness config (not just local)
✗ **Limited personality consistency checks** - No validation that agent system_prompts actually use their role definitions
✗ **No agent versioning** - No version field in AgentConfig
✗ **No meeting templates** - scenarios.py exists but not exposed in harness config
✗ **No llm_model override per agent** - All agents use same model (could allow budget/speed tradeoffs)
✗ **Sparse documentation of agent personas** - Each agent.json is standalone; no cross-reference matrix

---

### **11. Tech Stack Observations**

- **Python 3.9+** (uses `from __future__ import annotations`)
- **Pydantic v2** (model_validator, BaseModel features)
- **Type hints first** (Protocol pattern for LLMClient)
- **Stateless design** - follows Unix philosophy
- **Colorized output** - ANSI escape codes for terminal
- **Token estimation** - heuristic, no external tokenizer

**Language**: Primarily Chinese system prompts (agents are in Chinese), with English code comments

---

### **12. Sample Agent Personas (Actual Content)**

**gstack_munger.json**: Charlie Munger — Inversion thinking, multi-mental models, checklist discipline, incentive analysis
- ~350 char system prompt in Chinese

**real_powell.json**: The integrator — Cross-dimensional synthesis, cost-aware, rejects corporate speak
- ~2600 char system prompt in Chinese, highly detailed

**ecc_tdd_guide.json**: TDD expert — Red-Green-Refactor, test pyramid, test-as-docs philosophy
- ~1500 char system prompt (bilingual, with detailed disciplinary tone)

---

### **Summary Assessment**

This is a **production-ready multi-agent meeting system** with:

1. **Solid architecture**: Clear separation of concerns, protocol-based abstraction, stateless agents
2. **Rigorous testing**: 900+ lines of tests including deep context compression tests
3. **Rich persona library**: 30+ detailed agent configurations ready to use
4. **Smart state management**: Pydantic models enforce structure, max_rounds prevents infinite loops
5. **Professional UX**: Colored output, interactive mode, transcript + report saving
6. **Good documentation**: USAGE.md (23K), SKILL.md (180 lines), CLAUDE.md guidelines

**What it needs for "best practices" maturity**:
- Generic `settings.json` (not just `settings.local.json`)
- `AGENTS.md` catalog of all agents with strengths/use cases
- Structured hooks system for pre/post-meeting automation
- Agent versioning and consistency validation
- Feature declaration (feature_list.json)
- Cross-language consistency in prompts (some agents English, some Chinese)

The harness is **forward-thinking** (Powell integrator, context compression, human-in-the-loop) but still **emerging** (needs more structured configuration, documentation, and automation hooks).

Prompt:
I need to understand the harness setup in the /root/projects/meeting project. Please do a thorough exploration:

1. Read /root/projects/meeting/CLAUDE.md in full
2. Check if there's an AGENTS.md file in the project
3. Look for any .claude/ directory and its contents (settings.json, commands/, etc.)
4. Look for any other harness-related files (feature_list.json, init.sh, etc.)
5. Check the project's package.json or any config files to understand the tech stack
6. Look at the overall directory structure

I want to understand:
- What does the current harness look like in this real project?
- What's included and what's missing compared to best practices?
- What tech stack and patterns does this project use?

Report back with detailed findings including full file contents where relevant.


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Now I have comprehensive information from both projects. Let me update the task and move to the brainstorming phase - asking clarifying questions one at a time.

Key findings:
1. **learn-harness-engineering** teaches a comprehensive harness approach with 5 subsystems, progressive disclosure, WIP=1, feature lists as primitives, etc.
2. **meeting project** has a Python/multi-agent meeting system with CLAUDE.md, .claude/skills, .claude/settings.local.json, agents/ configs, but lacks AGENTS.md, feature_list.json, init.sh, etc.

3. Templates are available at docs/en/resources/templates/

The user wants to create a **universal harness template** that can be used as a starting point for ALL their Claude Code projects. Before I dive into building this, I need to clarify a few things - starting with whether the template should be tech-stack agnostic or tailored to specific languages, and how complete it should be versus minimal.