Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/akillness/oh-my-skills --skill diagnoseコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか?SkillsMP が現在取得できるファイルをダウンロードできます。
One-shot installer for the akillness/oh-my-gods agent skill bundle (80+ skills spanning agent-browser, agent-workflow, ai-research-skills, api-design, and the full god-skills catalog). Use when the user asks to add the oh-my-gods skill pack, bring in the AgenticSkills bundle, or wants every god-skill copied into Claude Code, Codex CLI, Antigravity/Gemini, and OpenCode in one step. Triggers on: AgenticSkills, agenticskills, oh-my-gods, god-skills, install oh-my-gods, bring in agentic skills bundle, install gods skills, add god skills.
Make any software agent-native with HKUDS CLI-Anything — route between four modes: install ready-made CLI harnesses via the CLI-Hub package manager (`pip install cli-anything-hub`, then `cli-hub list/search/info/install/launch`), give agents the autonomous discovery meta-skill (`npx skills add HKUDS/CLI-Anything --skill cli-hub-meta-skill`), generate a new harness from any codebase or GitHub repo via the 7-phase pipeline (`/plugin install cli-anything` → `/cli-anything <path>`), or iterate with `/cli-anything:refine`, `:test`, `:validate`. 40+ production harnesses (GIMP, Blender, LibreOffice, OBS, ComfyUI, Ollama, Godot, QGIS, …), 2,461 passing tests, Click CLIs with REPL + `--json` output. Use when agents must drive real desktop/server software without GUI automation. Triggers on: cli-anything, cli-hub, cli-anything-hub, agent-native cli, make software agent-native, cli harness generation, /cli-anything, harness refine, HKUDS cli.
Run Comet's Opik — open-source LLM observability, evaluation, and optimization — from one routing-first skill: install the Python/TypeScript SDK, stand up a server (Comet.com cloud, Docker Compose via `./opik.sh`, or Kubernetes/Helm), wire tracing through `@opik.track` or one of 50+ framework integrations (OpenAI, Anthropic, LangChain, LangGraph, LlamaIndex, CrewAI, DSPy, Ollama, Bedrock, Vercel AI SDK, …), score outputs with LLM-as-a-judge metrics (Hallucination, Moderation, Answer Relevance, Context Precision), and run Datasets/Experiments evaluations including PyTest CI gates. Use when the user wants LLM tracing, prompt evaluation, production LLM monitoring, agent optimization, or guardrails with Opik. Triggers on: opik, comet opik, opik configure, opik.sh, llm observability, llm tracing, llm as a judge, hallucination metric, prompt evaluation, opik dashboard, opik guardrails, agent optimizer.
SOC 職業分類に基づく
SKILL.md を表示中
| name | diagnose |
| description | Use this skill when > |
A six-phase loop for systematic bug investigation. The key insight: invest disproportionate effort in Phase 1. With a reliable feedback loop, phases 2–6 become mechanical.
debugginglog-analysistesting-strategiesCreate a fast, deterministic, automated pass/fail signal for the bug.
Goal: < 10 second feedback cycle
Signal: automated pass/fail, not manual inspection
Determinism: same input → same result every time
Ask yourself: "Can I run one command and know within 10 seconds if the bug is present?"
Do not proceed to Phase 2 until the feedback loop is reliable.
Confirm the failure is reproducible under controlled conditions.
Form ranked hypotheses about root cause.
H1 (most likely): [specific cause]
H2: [alternative cause]
H3: [edge case cause]
Run one discriminating check per hypothesis.
Apply the fix and verify it closes the loop.
# Phase 1: make the feedback loop
# Write a failing test or minimal repro script
# Phase 4: instrument at the narrowest point
console.error('[diagnose] value at boundary:', value)
# Phase 5: verify fix closes the loop
npm test -- --testPathPattern=failing-test
.agent-skills/skill-standardization/SKILL.md.agent-skills/skill-standardization/scripts/validate_skill.sh