Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/madappgang/claude-code/deep-analysisnpx skills add MadAppGang/claude-code --skill deep-analysisgit clone --depth 1 https://github.com/MadAppGang/claude-codeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00062 | $0.02794 |
| Opus 5 | $0.00031 | $0.01397 |
| Sonnet 5 | $0.00012 | $0.00559 |
| Haiku 4.5 | $0.00006 | $0.00279 |
Grade A, and why
deep-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 369 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Code Analysis
This Skill provides comprehensive codebase investigation capabilities using the codebase-detective agent with semantic search and pattern matching.
Prerequisites (MANDATORY)
╔══════════════════════════════════════════════════════════════════════════════╗
║ BEFORE INVOKING THIS SKILL ║
╠══════════════════════════════════════════════════════════════════════════════╣
║ ║
║ 1. INVOKE code-search-selector skill FIRST ║
║ → Validates tool selection (claudemem vs grep) ║
║ → Checks if claudemem is indexed ║
║ → Prevents tool familiarity bias ║
║ ║
║ 2. VERIFY claudemem status ║
║ → Run: claudemem status ║
║ → If not indexed: claudemem index -y ║
║ ║
║ 3. DO NOT start with Read/Glob ║
║ → Even if file paths are mentioned in the prompt ║
║ → Semantic search first, Read specific lines after ║
║ ║
╚══════════════════════════════════════════════════════════════════════════════╝
When to use this Skill
Claude should invoke this Skill when:
- User asks "how does [feature] work?"
- User wants to understand code architecture or patterns
- User is debugging and needs to trace code flow
- User asks "where is [functionality] implemented?"
- User needs to find all usages of a component/service
- User wants to understand dependencies between files
- User mentions: "investigate", "analyze", "find", "trace", "understand"
- User is exploring an unfamiliar codebase
- User needs to understand complex multi-file functionality
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 369 lines · 62 tokens per session scan A 724d1655c4fc
deep-analysis is a skill published in the GitHub repository MadAppGang/claude-code (279 stars, last pushed 5mo ago), licensed MIT. It adds 62 tokens to every session and 2,794 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…