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/ashermahonin/agentic-skills/analyze-codebasenpx skills add ashermahonin/agentic-skills --skill analyze-codebasegit clone --depth 1 https://github.com/ashermahonin/agentic-skillsWhat 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 | $0.00087 | $0.00462 |
| Opus 5 | $0.00044 | $0.00231 |
| Sonnet 5 | $0.00017 | $0.00092 |
| Haiku 4.5 | $0.00009 | $0.00046 |
Grade A, and why
analyze-codebase 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.
What it actually says
Analyze Codebase
Purpose
Slow the impulse to edit until the system has been understood. Produce an evidence-backed map of what exists, how it behaves, and where change would be risky.
Inputs
- Read the repo orientation files and build/test commands.
- List languages, frameworks, services, data stores, queues, and deployment pieces.
- Find entrypoints, critical flows, and ownership boundaries.
- Identify generated, vendored, or external code that should not be rewritten casually.
Decision process
- Map top-level directories to responsibilities.
- Trace the most important runtime flows from entrypoint to persistence or external boundary.
- Check build, test, lint, and local run instructions without changing source files.
- Identify hotspots: high-change files, large modules, unclear boundaries, test gaps, risky dependencies, and fragile contracts.
- Compare current architecture to the requested target and write migration risks before proposing edits.
- Stay read-only unless the user explicitly moves the work into implementation.
Decision boundaries
- Use Context7 MCP for current library, framework, platform, API, CLI, and configuration documentation whenever the task depends on external technology behavior.
Decision record
- Current-state scan
- Codebase map
- Hotspots and tech-debt list
- Current architecture summary
- Target gap notes
- Migration plan inputs
Ready when
- Back claims with file paths, commands, or observed behavior.
- Do not infer architecture from folder names alone.
- Separate actual current behavior from desired target behavior.
- Call out unknowns instead of smoothing them over.
Handoff
Hand off evidence, high-risk files, safe write boundaries, and validation commands to architecture or decomposition.
References
references/scan-checklist.md: Use this checklist when scanning an existing repository.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 55 lines · 87 tokens per session scan A 095d7c7b4a3c
analyze-codebase is a skill published in the GitHub repository ashermahonin/agentic-skills (10 stars, last pushed 9d ago), licensed MIT. It adds 87 tokens to every session and 462 once invoked, about $0.0004 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 2026-08-31.
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chat-perf
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