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 paulnsorensen/easy-cheese --skill skill-authoringgit clone --depth 1 https://github.com/paulnsorensen/easy-cheeseWrote 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/paulnsorensen/easy-cheese/skill-authoring)<a href="https://agentmods.dev/skills/paulnsorensen/easy-cheese/skill-authoring"><img src="https://agentmods.dev/badge/skills/paulnsorensen/easy-cheese/skill-authoring/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/paulnsorensen/easy-cheese/skill-authoring"><img src="https://agentmods.dev/badge/skills/paulnsorensen/easy-cheese/skill-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00074 | $0.01799 |
| Opus 5 | $0.00037 | $0.00899 |
| Sonnet 5 | $0.00015 | $0.00360 |
| Haiku 4.5 | $0.00007 | $0.00180 |
Grade A, and why
skill-authoring 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 10d 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 — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Authoring — easy-cheese conventions
This document codifies the skill-authoring rules for easy-cheese, drawn from obra/superpowers (CSO principle, Iron Law template, pressure-test gate) and Matt Pocock's skills repo (size budget, authoring checklist). It is the canonical reference for anyone adding or revising a skill.
Description rule (CSO)
The description is the only thing the harness shows the model when choosing a skill. Optimize it for triggering, not explanation.
The rule: sentence 1 = capability; sentence 2 = "Use when [triggering conditions]". No workflow summary, no pipeline-position prose, no feature list.
Rationale: a description that summarizes the skill's workflow creates a shortcut the model takes instead of reading the SKILL.md body. The skill then silently degrades to its own one-line description.
Constraints:
- Maximum 1024 characters (Codex rejects longer descriptions).
- Third-person, present tense.
- Triggering conditions name concrete phrases the user might say.
Test: strip the description and ask: could a model choose this skill over all others based on these words alone? If not, the triggers are missing.
Size budget
Keep SKILL.md bodies lean. The goal is a body a model can read in one pass without losing the thread.
The budget: 3,600 estimated tokens for the SKILL.md body (frontmatter excluded). At this repo's measured prose density that's roughly 150 lines, but tokens are the gated unit, not lines — line count misleads on dense prose: all 16 skills in this repo pass Anthropic's 500-line rule, while 8 exceed our 3,600-token budget on the same bodies.
Enforcement: CI runs this as a shrink-only ratchet —
.github/scripts/validate_skills.py, baselines recorded in
.github/skill-budgets.json, regenerated via just update-skill-budgets.
A skill already over budget when the ratchet was introduced is grandfathered
at its recorded value and may only shrink from there; a skill at or under
budget must stay under 3,600.
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.
- 10d ago First seen · 185 lines · 74 tokens per session scan A 03cc6d3f47fb
skill-authoring is a skill published in the GitHub repository paulnsorensen/easy-cheese (18 stars, last pushed today), licensed MIT. It adds 74 tokens to every session and 1,799 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.
Other skills, from other repositories
gentle-ai-collab-perfect
Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…
issue-creation
Trigger: issue creation, bug reports, feature requests, or issue approval. Create and triage GitHub issues from repository evidence.
sdd-tasks
Break an SDD change into implementation tasks. Trigger: orchestrator launches task planning for a change.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
cognitive-doc-design
Design docs that reduce cognitive load. Trigger: writing guides, READMEs, RFCs, onboarding, architecture, or review-facing docs.
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.