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 skills add knitli/toolshed --skill codexgit clone --depth 1 https://github.com/knitli/toolshedWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/knitli/toolshed/codex)<a href="https://agentmods.dev/skills/knitli/toolshed/codex"><img src="https://agentmods.dev/badge/skills/knitli/toolshed/codex/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/knitli/toolshed/codex"><img src="https://agentmods.dev/badge/skills/knitli/toolshed/codex.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00000 | $0.00351 |
| Opus 5.5 | $0.00000 | $0.00140 |
| Sonnet 5.5 | $0.00000 | $0.00070 |
| Haiku 4.5 | $0.00000 | $0.00035 |
Grade A, and why
.codex 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 1mo 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
Context Hygiene Skill
name
context-hygiene
description
Audit and maintain AI context files across tool ecosystems. Detects stale claims, contradictions between CLAUDE.md/AGENTS.md/Serena/Cursor/etc., and validates references against the actual codebase.
instructions
When activated, perform a context hygiene audit on the current repository:
1. Discovery
Scan for AI context files across all known tool ecosystems: CLAUDE.md, AGENTS.md, GEMINI.md, .claude/, .gemini/, .codex/, .cursor/, .serena/, .specify/, .roo/, .continue/, claudedocs/, specs/, plans/, docs/, info/, .mcp.json, .cursorrules, .windsurfrules, .continuerules, .clinerules, .aider.conf.yml
Report what you find as an inventory grouped by tool.
2. Staleness check
For each memory/instruction file, extract factual claims (paths, versions, symbols, counts, commands, dependencies) and validate them against the actual codebase. Report what's valid, what's stale, what's broken.
3. Drift detection
Compare memory files against each other to find contradictions and gaps. Flag where different tools have divergent views of the same project.
4. Summary
Produce a prioritized list of issues to fix, with specific file paths, line numbers, and recommended corrections.
After code changes
When you make significant changes to file structure, dependencies, versions, or architecture, proactively check whether any context files need updating. The most important files to keep current are the root-level memory files (CLAUDE.md, AGENTS.md).
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.
- 1mo ago First seen · 29 lines · 0 tokens per session scan A 73da82198706
.codex is a skill published in the GitHub repository knitli/toolshed (1 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 351 tokens. 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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