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/rakib-nyc/skillassay/format-pythonnpx skills add rakib-nyc/skillassay --skill format-pythongit clone --depth 1 https://github.com/rakib-nyc/skillassayWhat 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 | $0.00029 | $0.00044 |
| Opus 5 | $0.00015 | $0.00022 |
| Sonnet 5 | $0.00006 | $0.00009 |
| Haiku 4.5 | $0.00003 | $0.00004 |
Grade A, and why
format-python 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 yesterday.
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
Python formatting
Run ruff format.
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.
- yesterday First seen · 7 lines · 29 tokens per session scan A ad9d49f42f4a
format-python is a skill published in the GitHub repository rakib-nyc/skillassay (2 stars, last pushed 16d ago), licensed Apache-2.0. It adds 29 tokens to every session and 44 once invoked, about $0.0001 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.
Other skills, from other repositories
deep-init
Generate an agent-agnostic, two-tier context layer for a codebase — a lean, always-loaded CLAUDE.md plus a deep, on-demand .ai/docs/ layer (business rules, live DB schema + ORM drift, cross-component workflows, and the WHY: ADRs + a knowledge log), every claim grounded to file:line and verified to exist. Built for…
ruleblast
Git diff for AI agent repository instructions. Shows the blast radius of AGENTS.md and CLAUDE.md changes. Use when Git cannot show which agent inherited the edit, a Codex vs Claude Code split, or why one path inherited a stack.
agent-rules
Rewrites or audits text so it reads plainly: answer first, no preamble, no hype adjectives, no marketing voice, sentences short enough to read once. Applies a named ruleset plus ASD-STE100 Simplified Technical English. Use when asked to clean up, tighten, de-slop, or humanise a draft, a README, a release note, a…
context-diet
Measure and compact an oversized agent-context file (CLAUDE.md, .cursorrules, AGENTS.md, a system prompt) without losing rules, or safely run reversible bounded, reversible ablation when intentional/aggressive context removal is requested. Triggers: "CLAUDE.md too big", "over the char limit", "context file too large"…
contextdocs
Your AI agent maintains its own context files — a Claude Code plugin with an AGENTS-first model that covers Codex, Copilot, Cursor, Gemini, and 3 more tools. Signal Gate filtering, Context Guard hooks, health scoring, and MEMORY.md promotion.
review
Review a change and report actionable findings.