Provide implementations of advanced data structures
中文简介正在准备中。当前显示原文说明。
a5c-ai/babysitter18572026年9月17日 更新
免费在 GitHub 公开
spec-execution
6-phase iterative specification execution workflow covering implementation, testing, review, improvement, commit, and progress tracking with quality-gated convergence.
中文简介正在准备中。当前显示原文说明。
查看安装方法包含的文件（2）
- SKILL.md1.9 KB
- README.md377 B
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
- Read specification for requirements and architecture
- Implement each requirement following project conventions
- Add type definitions and JSDoc documentation
- Implement error handling for all failure modes
Phase 2: Test Writing
- Write unit tests for each module/function
- Write integration tests for API boundaries
- Cover all acceptance criteria from the specification
- Test edge cases and error paths
Phase 3: Code Review
- Verify all requirements are implemented
- Check acceptance criteria are tested
- Review architecture adherence
- Assess code quality
Phase 4: Iterative Improvement
- Address review findings
- Fix failing tests
- Resolve architecture deviations
- Re-verify quality (convergence loop, max 3 cycles)
Phase 5: Atomic Commit
- Group changes into logical atomic commits
- Descriptive messages following project conventions
- Separate production, test, and config changes
- Include specification reference
Phase 6: Progress Tracking
- Requirement completion percentage
- Test coverage summary
- Quality score report
- Remaining work identification
Quality Gate
Quality threshold defaults to 80. If not met after max improvement cycles, a human breakpoint is triggered for review.
When to Use
/spec:execute [file]slash command- After spec creation when ready to implement
Processes Used By
claudekit-spec-workflow(execute mode)
评价
还没有评价。欢迎分享你的使用感受。
评论
无需登录即可发表。欢迎分享使用感受、提问，或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
同一仓库的技能
Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.
中文简介正在准备中。当前显示原文说明。
a5c-ai/babysitter18572026年9月17日 更新
WASM-based instant code transforms for simple tasks, achieving 352x speedup over LLM inference with zero cost.
中文简介正在准备中。当前显示原文说明。
a5c-ai/babysitter18572026年9月17日 更新
Coordinate Crew (persistent) and Polecat (transient) agents using Gas Town's hook-based work distribution and GUPP principle.
中文简介正在准备中。当前显示原文说明。
a5c-ai/babysitter18572026年9月17日 更新
Generate visual representations of algorithm execution
中文简介正在准备中。当前显示原文说明。
a5c-ai/babysitter18572026年9月17日 更新
Hierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.
中文简介正在准备中。当前显示原文说明。
a5c-ai/babysitter18572026年9月17日 更新