Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add rjmurillo/ai-agents/plugin install project-toolkitWrote 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/rjmurillo/ai-agents/prose-self-check)<a href="https://agentmods.dev/skills/rjmurillo/ai-agents/prose-self-check"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/prose-self-check/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/rjmurillo/ai-agents/prose-self-check"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/prose-self-check.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 | $0.00104 | $0.03419 |
| Opus 5.5 | $0.00042 | $0.01368 |
| Sonnet 5.5 | $0.00021 | $0.00684 |
| Haiku 4.5 | $0.00010 | $0.00342 |
Grade A, and why
prose-self-check 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 18d 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 — 284 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prose Self-Check
Run this on prose you are about to emit. It catches AI-vernacular tells before
the artifact lands. It audits your OWN output, not human-authored text. It does
not touch code style (that is style-enforcement).
The layers are ordered by reader-trust, not by ease of detection. The cheap keyword signal (Layer 1) and the real reader-cited signal (Layers 2-4) point in different directions. Weight structural and semantic findings above lexical.
Empirical ranking from a public 89k-post study (John Carter, "I pulled ~90,000
Reddit posts about what makes writing sound like AI (Part 2)," r/ClaudeCode,
2026-06-22): em-dash 7.1% of reader cites, flat rhythm 4.0%, "not X, it's Y"
2.8%. Top keyword matches (however, moreover, nuanced) are ~0% reader-cited.
Triggers
prose self-checkaudit my writing for AI tellsdoes this read as AI-writtencheck this prose before I send it
When To Use
Run before emitting any prose artifact: session-log narrative, ADR context section, retrospective, PR body, issue body, design doc, agent-authored comment.
Skip for: code (use style-enforcement), pure data/config files, human-authored
text you were asked to preserve, and one-line acknowledgements with no prose.
Process
Layers 1 to 3 are pattern matches over text, so scripts run them. Layer 4 is the one no scanner can do, and it is where your attention belongs.
Start by running both helpers over the artifact:
python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/prose-self-check/scripts/prose_lint.py" FILE
python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/prose-self-check/scripts/burstiness.py" FILE
prose_lint.py covers Layers 1 and 2 and exits 1 on any high-severity
finding. Fix what it reports, re-run until it exits 0, then do Layer 4 by
hand. Do not scan for these tells by eye; you will miss some and spend
attention you need for Layer 4.
Layer 1: Lexical (weakest signal)
prose_lint.py runs this layer. It reports two tiers, and the tiering is the
point:
What ships with it
2 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.
- 18d ago Changed c2f56430b7a3
- 22d ago Changed · +6 lines 48219adc79d8
- 1mo ago First seen · 278 lines · 104 tokens per session scan A 555fd5815cdb
prose-self-check is a skill published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 104 tokens to every session and 3,419 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-03.
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