Borrowing it
Nothing to install: this file belongs to tbhb/vale-ai-tells. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tbhb/vale-ai-tells/main/.claude/skills/write-prose-fix/SKILL.mdgit clone --depth 1 https://github.com/tbhb/vale-ai-tellsWrote 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/tbhb/vale-ai-tells/write-prose-fix)<a href="https://agentmods.dev/skills/tbhb/vale-ai-tells/write-prose-fix"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/write-prose-fix/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/tbhb/vale-ai-tells/write-prose-fix"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/write-prose-fix.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 | $0.00026 | $0.02477 |
| Opus 5 | $0.00013 | $0.01239 |
| Sonnet 5 | $0.00005 | $0.00495 |
| Haiku 4.5 | $0.00003 | $0.00248 |
Grade A, and why
write-prose-fix 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 11d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reword until the prose lint passes, and change nothing else
Reword one file until its linters report nothing. Someone has already decided what the document says, and that part stays fixed. Change how it reads, and only as far as the findings require.
Context
!bash ${CLAUDE_SKILL_DIR}/scripts/context.sh $ARGUMENTS
The one rule
Leave the meaning alone. Every claim the document makes survives your pass intact, and so does every number, path, identifier, and name in it.
A finding you can only clear by saying something different is a finding you leave alone. Report it instead. Inventing a claim to please a linter is the worst outcome available here, because it reads as clean and puts words into the document that nobody wrote.
Reword. Don't rewrite.
Your inputs
$ARGUMENTS carries the target first, then the command that judges it. Anything after a -- is what the caller wants addressed, which on a second pass is the findings review-prose-fix returned. Treat those as the work: resolve each and say so.
The context below already ran the command and printed the document, so the findings and the text are both in front of you. Don't re-run the command to see them again.
The loop
- Read the findings in the preceding context. Count them.
- Fix the whole list in one editing pass, cheapest findings first, editing only the target.
- Run the lint command again. Compare the count.
Never re-run after one edit. Each round costs the same whether it clears one finding or twelve, and the session behind this skill spent half its Bash calls on linters it re-ran a fix at a time.
Stop at any of these:
- The command prints nothing, having printed something earlier. Read the next section before you trust that.
- The count fails to drop across two runs in a row.
- A finding you already cleared comes back. Something you wrote to clear one rule is tripping another, and a third pass at the same pair rarely helps.
- The loop has run five times.
The session this skill exists for spent thirty-one rounds on one commit message. Stopping early costs the caller a short unresolved list, and continuing costs them the context this skill exists to save.
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.
- 11d ago First seen · 183 lines · 26 tokens per session scan A da29ee08247b
write-prose-fix is a skill published in the GitHub repository tbhb/vale-ai-tells (92 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 2,477 once invoked, about $0.0001 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.
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