meta-build
Iteratively build an application or game phase-by-phase in clean subagents, reviewing each phase and refining the build-* skills / rules until each is optimal, then summarizing.
소스 정보
- 저장소
- adobe/data
- 최근 소스 활동
- 2026년 7월 24일 01:18
- 감지된 SKILL.md 언어
- 영어
- 스타
- 12
- 포크
- 8
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
SKILL.md 표시 중
SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- meta-build
- description
- Iteratively build an application or game phase-by-phase in clean subagents, reviewing each phase and refining the build-* skills / rules until each is optimal, then summarizing.
Purpose: exercise and **polish the build-* skills and the rules they reference**, using
a concrete app/game prompt as the test case. You are improving the *general* guidance,
not the one-off output.
## Procedure
1. Resolve `target` to its **ordered phases**. A composite target expands to its pipe —
`build-feature` → its `/build-*` layer steps; `build-application` / `build-game` →
`build-feature` for the base and each peer, then `build-app-entry`. A single
`build-<phase>` target is just that one phase.
2. For each phase, in order:
a. **Run it in a fresh subagent** with constrained context (`/x-subagent`): give the
subagent only the phase skill (`/<phase>`), the app/game prompt, and the files on
disk from prior phases — nothing about this loop or earlier attempts, so every
re-run differs only by any edits you made to the guidance.
b. **Review** the phase output in a subagent with `/review`.
c. If `/review` is not OPTIMAL: fix the **root cause in the guidance** — edit the
phase skill or a rule it references. Keep every edit **concise and general**:
improve it for all apps, never encode anything specific to this prompt. (For a
pure `code` slip with sound guidance, just re-run.) Do **not** hand-patch the
generated code.
d. Re-run from (a), up to `maxIterations` (default 4) attempts. Move to the next
phase once it reviews OPTIMAL — or the cap is hit (record that it did not converge).
e. Record: the phase, its iteration count, and every skill/rule file you edited.
3. **Final review** (read-only): run `/review` over the whole product. **Change nothing.**
Then summarize:
- per-phase iteration counts,
- which phase skills and which rules were edited, and why,
- overall outcome (which phases converged, which hit the cap).
Every phase runs in its own constrained subagent so re-executions during polishing stay
consistent — the edited skill/rule is the only variable between a phase's attempts.
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