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 commands/citedy/skills/skill-evalgit clone --depth 1 https://github.com/citedy/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 | $0.00035 | $0.00095 |
| Opus 5 | $0.00017 | $0.00048 |
| Sonnet 5 | $0.00007 | $0.00019 |
| Haiku 4.5 | $0.00003 | $0.00010 |
Grade A, and why
skill-eval 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.
What it actually says
Run the skill quality evaluator on the project's commands directory:
node .claude/skills/skill-quality-eval/scripts/run-eval.js
Read the output and present the results to the user. If there are failures, explain each issue and suggest fixes.
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 · 11 lines · 35 tokens per session scan A 9816c7fc8d9a
skill-eval is a command published in the GitHub repository citedy/skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 95 once invoked, about $0.0002 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 commands, from other repositories
pack-repo
Pack la codebase en un fichier AI-friendly (Repomix wrapper + fallback shell). Token counting inclus.
self-improve
Bootstrap and operate a self-improving agent workspace. Scaffolds .learnings/ and memory/ directories, captures errors and learnings during a session, detects recurring patterns, and promotes stable entries to project memory (CLAUDE.md, AGENTS.md, or references/). Also implements the Proactive Agent pillars — WAL…
second-opinion
Quick independent second opinion from one agent on a decision or approach.
skill-check
Show all installed skills, their sources, structure issues, and available updates.
parallel-feature-build
Orchestrated parallel implementation of complex features using multiple agents, with dependency-aware batching and synchronized progress tracking.
conjure-agent
Creates or updates a Claude Code agent definition (/.claude/agents/ .md or project-local).