一键在 Manus 中运行任何 Skill

analyze

Deep analysis and investigation for bugs, architecture issues, and risk hotspots. Use when the user asks to analyze, investigate, debug, or explain why something is failing.

在 Manus 中运行

概览

Deep analysis and investigation for bugs, architecture issues, and risk hotspots. Use when the user asks to analyze, investigate, debug, or explain why something is failing.

安装命令

npx skills add https://github.com/materialofair/claudecode-omc --skill analyze

复制此命令并粘贴到 Claude Code 中以安装该技能

来源

materialofair/claudecode-omc

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更新时间2026年4月1日 08:03

SKILL.md

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name	analyze
description	Deep analysis and investigation for bugs, architecture issues, and risk hotspots. Use when the user asks to analyze, investigate, debug, or explain why something is failing.
agent	debugger

Analyze

Use this skill for evidence-driven investigation before implementation.

Use When

The user asks to analyze, investigate, debug, root-cause, or explain failures
A fix has failed repeatedly and the team needs diagnosis first
You need architecture or dependency impact analysis before making changes

Workflow

Scope the target precisely.
Gather evidence:
- Read relevant files and tests
- Reproduce the issue when possible
- Capture exact errors and stack traces
Build and test hypotheses:
- Compare broken path vs working path
- Trace control/data flow
- Validate assumptions with commands
Conclude with ranked findings and concrete next actions.

Debug Protocol

Root-cause first. Do not jump to fixes.
After 3 failed hypotheses, expand scope and challenge the initial assumption.
Prefer user-observable behavior and reproducible evidence over speculation.

Output Format

Summary (2-3 sentences)
Key findings (ranked by impact)
Evidence (file references, command output, repro notes)
Recommended next actions (minimal-risk order)

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swiftui-expert-skill

materialofair/claudecode-omc

Use when writing, reviewing, or refactoring SwiftUI code for iOS or macOS, including state management, view composition, performance, Liquid Glass adoption, or Instruments `.trace` capture/analysis for hangs, hitches, CPU hotspots, or excessive view updates.

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h5-to-swiftui

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Convert an H5 / web app's source into a native SwiftUI iOS app by native rewrite (NOT a WebView shell, NOT a transpiler). Use when the user wants to port, re-implement, or migrate a web/H5 frontend to native SwiftUI with high visual fidelity, asks to "turn this web app into a real iOS app", or wants a measured render-diff convergence loop against a browser baseline. Auto-detects the web stack (v1: vanilla + React; other stacks are detected then gated, not guessed), extracts design tokens, calibrates a cross-renderer fidelity floor, rewrites per component, and drives a bounded render→diff→correct loop that reports a quantified visual residual plus an independent judge verdict. It does NOT promise literal pixel-identity: cross-renderer differences impose a measured floor it reports honestly. Triages canvas/WebGL/complex-animation/3rd-party-SDK/backend surfaces instead of silently emitting wrong code.

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prompt-optimizer

materialofair/claudecode-omc

Analyze raw prompts, identify intent and gaps, match ECC components (skills/commands/agents/hooks), and output a ready-to-paste optimized prompt. Advisory role only — never executes the task itself. TRIGGER when: user says "optimize prompt", "improve my prompt", "how to write a prompt for", "help me prompt", "rewrite this prompt", or explicitly asks to enhance prompt quality. Also triggers on Chinese equivalents: "优化prompt", "改进prompt", "怎么写prompt", "帮我优化这个指令". Specially handles short Chinese bug reports (the dominant real-world use case): runs Bug Report Triage to extract repro/expected/actual/environment, asks up to 3 clarifying questions if ≤ 2 fields are present, and inserts systematic-debugging as a hard prerequisite before any code change. DO NOT TRIGGER when: user wants the task executed directly, or says "just do it" / "直接做". DO NOT TRIGGER when user says "优化代码", "优化性能", "optimize performance", "optimize this code" — those are refactoring/performance tasks, not prompt optimization (unless the user exp

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conductor-distill

materialofair/claudecode-omc

Distill methodology from superpowers and BMAD-METHOD docs into the active conductor track's spec.md / plan.md / review.md as intent-layer overlays. Use when user asks to "distill superpowers into conductor", "把 superpowers/bmad 提炼到 conductor", "import method docs to track", "seed conductor with brainstorming/TDD/verification gates", or "feed BMAD PRD/architecture/story/QA principles into the track". Writes only inside marker blocks so it never competes with code-derived facts and re-runs cleanly. DO NOT use for general superpowers invocation, code refactors, or to summarize this codebase.

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de-ai-writing

materialofair/claudecode-omc

Humanize PROSE drafts — articles, blog posts, public-account 公众号 copy, marketing copy, sermons, technical write-ups — that read like an LLM produced them. Chinese-first, supports zh/en mixed text. Cross-checks output against the Wikipedia "Signs of AI writing" taxonomy before delivery. TRIGGER when user asks to remove AI tone or humanize TEXT/DRAFT/ARTICLE/COPY/稿/文章/帖子: "去 AI 味", "去ai味", "降低机器感", "改得像真人写的", "不要 AI 腔", "humanize this draft", "humanize this article", "remove AI tone", "de-ai this writing". DO NOT TRIGGER for code cleanup, dead-code removal, AI-generated source code, or "deslop" of codebases — those belong to ai-slop-cleaner. DO NOT TRIGGER for prompt optimization — that is prompt-optimizer.

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guideline-optimizer

materialofair/claudecode-omc

Maintainer-only workflow for semantically optimizing OMC guideline sources into a concise canonical .local/guidelines/CLAUDE.md output. Use when curating external prompt-guideline repos such as andrej-karpathy-skills.

2026-04-231

来源

materialofair

materialofair/claudecode-omc

打开 GitHub 仓库查看创作者相关仓库

安装命令

下载

在 Manus 中运行

适用职业SOC

软件开发工程师计算机与数学类职业15-1252L4

name	analyze
description	Deep analysis and investigation for bugs, architecture issues, and risk hotspots. Use when the user asks to analyze, investigate, debug, or explain why something is failing.
agent	debugger

Analyze

Use this skill for evidence-driven investigation before implementation.

Use When

The user asks to analyze, investigate, debug, root-cause, or explain failures
A fix has failed repeatedly and the team needs diagnosis first
You need architecture or dependency impact analysis before making changes

Workflow

Scope the target precisely.
Gather evidence:
- Read relevant files and tests
- Reproduce the issue when possible
- Capture exact errors and stack traces
Build and test hypotheses:
- Compare broken path vs working path
- Trace control/data flow
- Validate assumptions with commands
Conclude with ranked findings and concrete next actions.

Debug Protocol

Root-cause first. Do not jump to fixes.
After 3 failed hypotheses, expand scope and challenge the initial assumption.
Prefer user-observable behavior and reproducible evidence over speculation.

Output Format

Summary (2-3 sentences)
Key findings (ranked by impact)
Evidence (file references, command output, repro notes)
Recommended next actions (minimal-risk order)