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/hamsurang/kit/library-analyzernpx skills add hamsurang/kit --skill library-analyzergit clone --depth 1 https://github.com/hamsurang/kitWhat 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 | $0.00072 | $0.02304 |
| Opus 5 | $0.00036 | $0.01152 |
| Sonnet 5 | $0.00014 | $0.00461 |
| Haiku 4.5 | $0.00007 | $0.00230 |
Grade A, and why
library-analyzer 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 2d 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 — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Library Analyzer
Analyze an open-source library for contribution readiness. Produces a structured Markdown report covering codebase structure, lifecycle, and contribution paths.
Contents
- When This Skill Activates
- Step 1: Input Parsing
- Step 2: Data Collection
- Step 3: Parallel Analysis
- Step 4: Result Assembly
- Iron Rules
When This Skill Activates
- User wants to contribute to an open-source library or project
- User says "analyze this library", "I want to contribute to X", "기여하고 싶다"
- User asks for a "contribution analysis" or "contribution readiness" report
Do NOT activate when:
- User asks "how does X work?" or "what is the architecture of X?" → use
deepwiki-cli - User wants to understand a codebase without contributing intent → use
deepwiki-cli
Step 1: Input Parsing
Parse the target from $ARGUMENTS or ask the user with AskUserQuestion.
| Input Format | Action |
|---|---|
https://github.com/owner/repo |
URL mode |
owner/repo |
URL mode (shorthand, treat as GitHub) |
/path/to/dir or ./path |
Local mode |
react (bare name) |
Reject: "Please use owner/repo format (e.g., facebook/react)" |
Validate the input:
- URL mode: Run
which deepwiki-clivia Bash.- If installed → proceed with deepwiki-cli data collection.
- If NOT installed → tell the user:
"deepwiki-cli is required for URL mode. Install with
cargo install deepwiki-cli, or clone the repo locally and provide the local path instead."
- Local mode: Verify the path exists and is a directory.
- If not → report the error and stop.
Extract owner/repo for issue collection:
- URL mode: parse from the URL or shorthand directly.
- Local mode: run
git -C <path> remote get-url originand matchgithub.com[:/]owner/repo.- If no GitHub remote → issues will be skipped (note this to the user).
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.
- 2d ago First seen · 235 lines · 72 tokens per session scan A 488d1f58a50d
library-analyzer is a skill published in the GitHub repository hamsurang/kit (19 stars, last pushed 4mo ago), licensed MIT. It adds 72 tokens to every session and 2,304 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 2026-08-30.
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