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 AnastasiyaW/codex-claude-code-config --skill humanize-englishgit clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-configWrote 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/anastasiyaw/codex-claude-code-config/humanize-english)<a href="https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/humanize-english"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/humanize-english/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/anastasiyaw/codex-claude-code-config/humanize-english"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/humanize-english.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 | $0.00086 | $0.01485 |
| Opus 5 | $0.00043 | $0.00743 |
| Sonnet 5 | $0.00017 | $0.00297 |
| Haiku 4.5 | $0.00009 | $0.00148 |
Grade A, and why
humanize-english 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 2d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Clear, Natural English Editing
Improve the reader's understanding, not a detector score. A good reference can have repeated terminology, regular tables, definitions and no anecdote. Keep the user's intended voice and the destination's format.
Facts Are Not Style Material
- Preserve supplied numbers, units, dates, versions, names, citations, negation, uncertainty and claim scope. Do not silently update a historical date.
- Never invent a count, quote, interview, personal experience, experiment, failure, comparison or source to make prose more vivid.
- Add specificity only when the supporting evidence supplies it. If no measurement exists, retain uncertainty or remove an unsupported claim. An unsupplied number is not an improvement over a vague quantity.
- Label illustrative scenarios as hypothetical. Do not present them as a real case study or treat their invented values as proof of a product claim.
- Preserve identifiers, executable code and technical obligations. Words such as may, must, can and will are not interchangeable style alternatives.
- Reuse provided facts without asking the user to repeat them. Research a material factual gap when research is in scope; otherwise identify the gap without manufacturing an answer or blocking supported edits.
Match the Genre
| Genre | Useful editing | Avoid forcing |
|---|---|---|
| technical reference | exact terms, clear conditions, scannable structure | slang, story openings, rhetorical questions, sales CTA |
| explanation/tutorial | prerequisites and action/result sequence | an untested command described as verified |
| analysis | separate observation, inference and limits | stronger causal claims than the evidence supports |
| personal narrative | the author's supplied experiences and voice | invented first-person testimony |
| marketing | a supported benefit and relevant next action | fabricated testimonials, percentages or guarantees |
Contractions, fragments, humour, analogies and direct address are options, not quotas. Use them when they fit the audience and improve comprehension. Parallel lists and consistent terminology can be desirable in documentation.
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.
- 2d ago Changed · -156 lines · -60 tokens per session 334295489dc2
- 6d ago First seen · 286 lines · 146 tokens per session scan A d24fc3861f02
humanize-english is a skill published in the GitHub repository AnastasiyaW/codex-claude-code-config (149 stars, last pushed yesterday), licensed MIT. It adds 86 tokens to every session and 1,485 once invoked, about $0.0004 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 2026-09-03.
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