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Implements Anthropic's March 2026 harness design pattern — a multi-agent architecture that separates generation from evaluation, creating an adversarial feedback loop that produces production-quality applications. Components: - 3 agent definitions (planner, generator, evaluator) - 1 skill with full documentation (skills/gan-style-harness/) - 2 commands (gan-build for full apps, gan-design for frontend) - 1 shell orchestrator (scripts/gan-harness.sh) - Examples and configuration reference Based on: https://www.anthropic.com/engineering/harness-design-long-running-apps Co-authored-by: Hao Chen <haochen806@gmail.com>
100 lines
3.1 KiB
Markdown
100 lines
3.1 KiB
Markdown
Parse the following from $ARGUMENTS:
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1. `brief` — the user's one-line description of what to build
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2. `--max-iterations N` — (optional, default 15) maximum generator-evaluator cycles
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3. `--pass-threshold N` — (optional, default 7.0) weighted score to pass
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4. `--skip-planner` — (optional) skip planner, assume spec.md already exists
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5. `--eval-mode MODE` — (optional, default "playwright") one of: playwright, screenshot, code-only
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## GAN-Style Harness Build
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This command orchestrates a three-agent build loop inspired by Anthropic's March 2026 harness design paper.
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### Phase 0: Setup
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1. Create `gan-harness/` directory in project root
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2. Create subdirectories: `gan-harness/feedback/`, `gan-harness/screenshots/`
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3. Initialize git if not already initialized
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4. Log start time and configuration
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### Phase 1: Planning (Planner Agent)
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Unless `--skip-planner` is set:
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1. Launch the `gan-planner` agent via Task tool with the user's brief
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2. Wait for it to produce `gan-harness/spec.md` and `gan-harness/eval-rubric.md`
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3. Display the spec summary to the user
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4. Proceed to Phase 2
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### Phase 2: Generator-Evaluator Loop
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```
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iteration = 1
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while iteration <= max_iterations:
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# GENERATE
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Launch gan-generator agent via Task tool:
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- Read spec.md
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- If iteration > 1: read feedback/feedback-{iteration-1}.md
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- Build/improve the application
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- Ensure dev server is running
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- Commit changes
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# Wait for generator to finish
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# EVALUATE
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Launch gan-evaluator agent via Task tool:
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- Read eval-rubric.md and spec.md
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- Test the live application (mode: playwright/screenshot/code-only)
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- Score against rubric
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- Write feedback to feedback/feedback-{iteration}.md
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# Wait for evaluator to finish
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# CHECK SCORE
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Read feedback/feedback-{iteration}.md
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Extract weighted total score
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if score >= pass_threshold:
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Log "PASSED at iteration {iteration} with score {score}"
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Break
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if iteration >= 3 and score has not improved in last 2 iterations:
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Log "PLATEAU detected — stopping early"
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Break
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iteration += 1
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```
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### Phase 3: Summary
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1. Read all feedback files
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2. Display final scores and iteration history
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3. Show score progression: `iteration 1: 4.2 → iteration 2: 5.8 → ... → iteration N: 7.5`
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4. List any remaining issues from the final evaluation
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5. Report total time and estimated cost
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### Output
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```markdown
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## GAN Harness Build Report
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**Brief:** [original prompt]
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**Result:** PASS/FAIL
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**Iterations:** N / max
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**Final Score:** X.X / 10
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### Score Progression
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| Iter | Design | Originality | Craft | Functionality | Total |
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|------|--------|-------------|-------|---------------|-------|
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| 1 | ... | ... | ... | ... | X.X |
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| 2 | ... | ... | ... | ... | X.X |
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| N | ... | ... | ... | ... | X.X |
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### Remaining Issues
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- [Any issues from final evaluation]
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### Files Created
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- gan-harness/spec.md
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- gan-harness/eval-rubric.md
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- gan-harness/feedback/feedback-001.md through feedback-NNN.md
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- gan-harness/generator-state.md
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- gan-harness/build-report.md
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```
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Write the full report to `gan-harness/build-report.md`.
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