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 affinagegit 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/affinage)<a href="https://agentmods.dev/skills/paulnsorensen/easy-cheese/affinage"><img src="https://agentmods.dev/badge/skills/paulnsorensen/easy-cheese/affinage/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/affinage"><img src="https://agentmods.dev/badge/skills/paulnsorensen/easy-cheese/affinage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 262 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00056 | $0.03234 |
| Opus 5 | $0.00028 | $0.01617 |
| Sonnet 5 | $0.00011 | $0.00647 |
| Haiku 4.5 | $0.00006 | $0.00323 |
Grade A, and why
affinage 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.
How it starts
The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/affinage
Act on existing claims about a PR.
Claims can come from reviewers, CI checks, or merge conflicts.
Grade each claim through the /age lens.
Send accepted claims to /cure.
/affinage always grades claims that exist on the PR.
Its entry path controls whether it also finds new /age findings:
- Standalone — The user starts
/affinage <pr>withouthandoff_context. Run/ageon the PR diff unless the user passes--no-age. Add the new findings to the same report. - Chained —
/cookor/curesupplieshandoff_context. Skip the fresh review because/agealready ran in this chain.
See ## Fresh review for the entry rule.
See ## Merge-conflict resolution for the conflict path.
Inputs
/affinage [<pr-ref>] [--auto --stake <floor>] [--plate] [--safe] [--open-pr] [--hard] [--full] [--include-outdated]
<pr-ref> accepts a PR number, a PR#<n> reference, or a full GitHub PR URL.
Extract the integer before you call pr-status.
The command accepts only the integer.
If no reference exists, run gh pr view --json number on the current branch.
Flags:
--auto --stake <floor>— Run without selection prompts.<floor>acceptsblocker,high,medium+, orall. Bare--autouses themedium+default floor. Use the same floor rules as/cure. Send/cure --auto --stake <floor>. Post replies without prompts. Seereferences/auto-mode.md.--safe— Add gates before cure selection and conflict resolution. This flag does not remove the default reply gate.--open-pr— Let terminal/plateopen a new PR when no PR exists. Without this flag,/plateonly updates an open PR.--plate— Run--auto --stake medium+ --open-pr. Grade the claims. Cure the selected findings. Post the replies. Then run/plate. An explicit--stake <floor>replacesmedium+.--hard— Pass the metacognitive gate flag to terminal/plate.--full— Show all low findings when at least 10 low findings exist.--include-outdated— Include outdated review threads.--no-age— Skip the fresh review in standalone mode. This flag has no effect in chained mode.
What ships with it
7 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.
- yesterday Changed 30dad252540c
- 5d ago Changed · +151 lines · -36 tokens per session 26827787cea5
- 7d ago Changed · +2 lines 8340383552d8
- 11d ago First seen · 141 lines · 92 tokens per session scan A f86e3410c180
affinage is a skill published in the GitHub repository paulnsorensen/easy-cheese (18 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 3,234 once invoked, about $0.0003 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…
branch-pr
Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
chained-pr
Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.
ship
Use when code is ready to ship — creates PRs, merges, deploys, and verifies. Handles the full PR-to-production pipeline. Triggers on /ship.
release-readiness
Use after review/qa/security/license-audit/privacy-check to compose a release decision before /ship. Returns OK only when all required upstream evidence is present and clean. Triggers on /release-readiness.