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 jerseycheese/agent-skills --skill plain-language-auditgit clone --depth 1 https://github.com/jerseycheese/agent-skillsWrote 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/jerseycheese/agent-skills/plain-language-audit)<a href="https://agentmods.dev/skills/jerseycheese/agent-skills/plain-language-audit"><img src="https://agentmods.dev/badge/skills/jerseycheese/agent-skills/plain-language-audit/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/jerseycheese/agent-skills/plain-language-audit"><img src="https://agentmods.dev/badge/skills/jerseycheese/agent-skills/plain-language-audit.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 | $0.00161 | $0.02351 |
| Opus 5 | $0.00081 | $0.01175 |
| Sonnet 5 | $0.00032 | $0.00470 |
| Haiku 4.5 | $0.00016 | $0.00235 |
Grade A, and why
plain-language-audit 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plain Language Audit
A sweep for text that's harder to read than it needs to be — jargon standing in for a plainer word, AI writing tells that make prose sound generated instead of written, and verbosity that says less in more words. Covers code comments, docstrings, markdown docs, and user-facing UI copy/strings.
This is the prose counterpart to doc-rot (which fixes docs that are wrong) and code-health-audit (which fixes code that's overengineered) — this one fixes text that's hard to read, whether or not it's accurate.
Developer-facing text (comments, docstrings, internal docs, PR/issue prose) gets the full treatment: plain language, AI-tell removal, tightening, and — where genuinely a rewrite rather than a mechanical swap — the user's own voice (apply the voice skill, canon at ~/.agents/voice.local.md).
User-facing UI copy (button labels, error messages, empty states, in-app strings) gets plain language, AI-tell removal, and tightening only — never the developer-voice rewrite. It's a different audience with its own conventions (see the design:ux-copy skill if one's installed); don't impose "sounds like Jack" on a "Forgot password?" link. UI copy findings always go in the judgment-call bucket below, never auto-fixed.
This skill is for auditing text that already lives in a repo. If the actual ask is "make this pasted paragraph more concise" or "tighten my last reply" with no file/repo target, that's a direct edit to the text in front of you — just do it. Don't run git pre-flight, don't create or touch an audit-memory file, don't treat a standalone rewrite request as a repo sweep.
Pre-flight
Per the user's git workflow: git fetch && git status, confirm the right base branch and that it's synced. Then scope it — don't boil the ocean. State what's in range (a directory, a domain, recently-touched files) and confirm before sweeping a whole repo. Keep that confirmed scope as a variable through the rest of the run — every search below runs against it, not the whole tree.
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 · 109 lines · 161 tokens per session scan A 8d7664df3504
plain-language-audit is a skill published in the GitHub repository jerseycheese/agent-skills (1 stars, last pushed 8d ago), licensed MIT. It adds 161 tokens to every session and 2,351 once invoked, about $0.0008 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
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chorus-council
Run an LLM council — Claude (correctness), Gemini (edge cases), Cursor (integration), Kilo (maintainability), and you (scope) tackle the same task in parallel. Use when the user wants multiple independent perspectives on a decision, approach, or problem.
chorus-vote
Put a yes/no proposition to five agents and tally YES / NO / ABSTAIN votes when the user wants a quick decision signal.
chorus-parallel-debug
Parallel root-cause hypotheses from multiple agents for a reported bug. Use when the user says "parallel debug", "chorus debug", "multiple hypotheses", or "debug with all agents".
chorus-parallel-review
Parallel code review of the current git diff from multiple agents — Claude (correctness/security), Gemini (edge cases), Cursor (integration), Kilo (maintainability), and you (scope/simplicity). Use when the user says "parallel review", "review with all agents", or "chorus review".