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/gan-build

Run a generator/evaluator build loop for implementation tasks with bounded iterations and scoring.

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ecc
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> /plugin install ecc@ecc

Command definition

gan-build.md
description: Run a generator/evaluator build loop for implementation tasks with bounded iterations and scoring.

Parse the following from $ARGUMENTS: 1. `brief` — the user's one-line description of what to build 2. `--max-iterations N` — (optional, default 15) maximum generator-evaluator cycles 3. `--pass-threshold N` — (optional, default 7.0) weighted score to pass 4. `--skip-planner` — (optional) skip planner, assume spec.md already exists 5. `--eval-mode MODE` — (optional, default "playwright") one of: playwright, screenshot, code-only

GAN-Style Harness Build

This command orchestrates a three-agent build loop inspired by Anthropic's March 2026 harness design paper.

Phase 0: Setup

1. Create `gan-harness/` directory in project root 2. Create subdirectories: `gan-harness/feedback/`, `gan-harness/screenshots/` 3. Initialize git if not already initialized 4. Log start time and configuration

Phase 1: Planning (Planner Agent)

Unless `--skip-planner` is set: 1. Launch the `gan-planner` agent via Task tool with the user's brief 2. Wait for it to produce `gan-harness/spec.md` and `gan-harness/eval-rubric.md` 3. Display the spec summary to the user 4. Proceed to Phase 2

Phase 2: Generator-Evaluator Loop

iteration = 1
while iteration <= max_iterations:

    # GENERATE
    Launch gan-generator agent via Task tool:
    - Read spec.md
    - If iteration > 1: read feedback/feedback-{iteration-1}.md
    - Build/improve the application
    - Ensure dev server is running
    - Commit changes

    # Wait for generator to finish

    # EVALUATE
    Launch gan-evaluator agent via Task tool:
    - Read eval-rubric.md and spec.md
    - Test the live application (mode: playwright/screenshot/code-only)
    - Score against rubric
    - Write feedback to feedback/feedback-{iteration}.md

    # Wait for evaluator to finish

    # CHECK SCORE
    Read feedback/feedback-{iteration}.md
    Extract weighted total score

    if score >= pass_threshold:
        Log "PASSED at iteration {iteration} with score {score}"
        Break

    if iteration >= 3 and score has not improved in last 2 iterations:
        Log "PLATEAU detected — stopping early"
        Break

    iteration += 1

Phase 3: Summary

1. Read all feedback files 2. Display final scores and iteration history 3. Show score progression: `iteration 1: 4.2 → iteration 2: 5.8 → ... → iteration N: 7.5` 4. List any remaining issues from the final evaluation 5. Report total time and estimated cost

Output

## GAN Harness Build Report

**Brief:** [original prompt]
**Result:** PASS/FAIL
**Iterations:** N / max
**Final Score:** X.X / 10

### Score Progression
| Iter | Design | Originality | Craft | Functionality | Total |
|------|--------|-------------|-------|---------------|-------|
| 1 | ... | ... | ... | ... | X.X |
| 2 | ... | ... | ... | ... | X.X |
| N | ... | ... | ... | ... | X.X |

### Remaining Issues
- [Any issues from final evaluation]

### Files Created
- gan-harness/spec.md
- gan-harness/eval-rubric.md
- gan-harness/feedback/feedback-001.md through feedback-NNN.md
- gan-harness/generator-state.md
- gan-harness/build-report.md

Write the full report to `gan-harness/build-report.md`.

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Your agent can write code, but ECC gives it a coordinated engineering system and toolbox: it plans before it builds, verifies changes with tests, reviews its own work from a fresh context, remembers what matters, and turns repeated wins into reusable skills

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