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/codex-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/codex-write-prose-fix)<a href="https://agentmods.dev/skills/tbhb/vale-ai-tells/codex-write-prose-fix"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/codex-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/codex-write-prose-fix"><img src="https://agentmods.dev/badge/skills/tbhb/vale-ai-tells/codex-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 | $0.00044 | $0.00374 |
| Opus 5 | $0.00022 | $0.00187 |
| Sonnet 5 | $0.00009 | $0.00075 |
| Haiku 4.5 | $0.00004 | $0.00037 |
Grade A, and why
codex-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 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.
What it actually says
Fix prose and nothing else
The delegation prompt supplies the repository root, target, workflow state, and lint command. Start by running .agents/skills/codex-write-prose-fix/scripts/context.sh <target> <state> <lint command> from that root. It prints the document, findings, scope probe, and saved review notes.
Preserve every claim, qualifier, number, path, identifier, and name. Reword, but don't rewrite. Only the target's prose may change. Leave linter configuration, dictionaries, every other file, fenced code, paths, and backticked identifiers untouched. Don't add suppression comments. Preserve the target’s wrapping convention.
Run mise run fix-prose-replacements <target> first. Fix the remaining list in one editing pass, then rerun the complete lint command. Stop when it's clean or after five rounds. Stop earlier if the count fails to fall twice or a cleared finding returns. Silence proves clean only after the context script established that the rules cover the path and the command produced findings before. Report a rule that no wording can clear without changing meaning.
Use apply_patch for edits. Return exactly one form:
PROSE: CLEAN
changed: <one line per class of edit>
PROSE: PARTIAL
changed: <summary or nothing>
unresolved:
1. [<rule>] <line>: <exact text>
why: <cost of clearing it>
PROSE: BLOCKED
reason: <what stopped the work>
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.
- 10d ago First seen · 37 lines · 44 tokens per session scan A ae42b51e2abc
codex-write-prose-fix is a skill published in the GitHub repository tbhb/vale-ai-tells (91 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 374 once invoked, about $0.0002 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
anti-slop
Remove AI slop from any voice-bearing prose — original posts, threads, articles, long-form, emails, docs, READMEs, marketing copy, bios, scripts. Use when drafting text meant to sound like a specific person or brand, when rewriting text that reads generic, corporate, or AI-generated, or when asked to humanize…
kill-slop
Audit a file or draft for AI slop and off-voice lines against the author's bound voice, report findings with in-voice swaps, then apply approved fixes. Use when the user says "kill slop", "/kill-slop [file]", "find the slop in this", "audit this for slop", or wants a deck, article, page, or draft cleaned to sound like…
humanizer
Humanize and de-slop AI-sounding prose while preserving meaning, specific detail, and genuine human quirks. When a voice sample or style profile is available, rewrite in that writer's actual voice. Remove recurring AI tells such as inflated significance, stock vocabulary, uniform rhythm, excessive hedging, formulaic…
authenticity-check
Score how authentically text reads as a real human author's work, flag spans that read as AI-generated, AI-templated, or generically derivative, and run a separate read-only scan for suspicious Unicode provenance carriers. Return an authenticity band, a 0-100 score, provenance signals, and span-level reasons. Use when…
ai-slop-detector
Universal prose audit. Scores writing on TWO axes — AI-Slop (does this read like AI wrote it?) and Comprehension (can a fresh reader follow this?). Use PROACTIVELY as a mandatory final QA pass on ANY prose generated for humans to read — every email (internal or external), proposal, report, status update, blog post…
humanizer-czech
Odstraň znaky AI-generovaného psaní z českého textu. Použij při editaci nebo revizi textu, aby zněl přirozeněji a lidštěji. Detekuje a opravuje 27 vzorců včetně: nafouklého významu, propagačního jazyka, anglického slovosledu, kalků, nominalizace, monotónního rytmu, nadužívání spojek, typických českých AI klišé…