UNPKG

aiwg

Version:

Cognitive architecture for AI-augmented software development with structured memory, ensemble validation, and closed-loop correction. FAIR-aligned artifacts, 84% cost reduction via human-in-the-loop, standards adopted by 100+ organizations.

82 lines (61 loc) 2.26 kB
# auto-test-execution Automatically execute tests when code-generating agents write to source files, enforcing the execute-before-return pattern. ## Triggers - Agent writes to `src/**/*.ts` - Agent writes to `src/**/*.js` - Agent writes to `src/**/*.py` - Agent writes to `**/*.go` - Agent writes to `**/*.rs` - "run tests" - "execute feedback" - "verify my changes" ## Purpose This skill enforces the MetaGPT executable feedback pattern: code-generating agents must execute tests before returning results to the user. It activates automatically when agents modify source code files. ## Behavior When triggered, this skill: 1. **Detect modified files**: - Track which source files the agent has written to - Identify the relevant test framework 2. **Find related tests**: - Look for test files matching the modified source - Convention: `src/foo/bar.ts` -> `test/unit/foo/bar.test.ts` - If no tests exist, prompt agent to generate them 3. **Execute tests**: - Run the project's test command focused on relevant tests - Capture results: passed, failed, errors 4. **Handle results**: - All pass: Allow agent to return results - Failures: Trigger debug-and-retry loop (max 3 attempts) - Persistent failures: Escalate with debug memory context 5. **Update debug memory**: - Record session in `.aiwg/ralph/debug-memory/sessions/` - Extract patterns for future reference ## Activation Conditions ```yaml activation: always_active_for: - software-implementer - debugger - test-engineer triggered_by: - file_write: patterns: - "src/**/*.ts" - "src/**/*.js" - "src/**/*.py" - "**/*.go" - "**/*.rs" skip_when: - test_files_only: true - documentation_only: true - configuration_only: true ``` ## Integration This skill uses: - `project-awareness`: Detect test framework and configuration - Debug memory at `.aiwg/ralph/debug-memory/` for pattern learning ## References - @.claude/rules/executable-feedback.md - Feedback rules - @.aiwg/ralph/docs/executable-feedback-guide.md - Guide - @agentic/code/addons/ralph/schemas/debug-memory.yaml - Memory schema - @.aiwg/research/findings/REF-013-metagpt.md - Research foundation