Borrowing it
Nothing to install: this file belongs to andrzejchm/fdb. 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/andrzejchm/fdb/main/.agents/skills/humanizing-ai-text/SKILL.mdgit clone --depth 1 https://github.com/andrzejchm/fdbWrote 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/andrzejchm/fdb/humanizing-ai-text)<a href="https://agentmods.dev/skills/andrzejchm/fdb/humanizing-ai-text"><img src="https://agentmods.dev/badge/skills/andrzejchm/fdb/humanizing-ai-text/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/andrzejchm/fdb/humanizing-ai-text"><img src="https://agentmods.dev/badge/skills/andrzejchm/fdb/humanizing-ai-text.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 | $0.00062 | $0.01757 |
| Opus 5.5 | $0.00025 | $0.00703 |
| Sonnet 5.5 | $0.00012 | $0.00351 |
| Haiku 4.5 | $0.00006 | $0.00176 |
Grade A, and why
humanizing-ai-text 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 24d 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rewrite prose so it sounds like a direct human teammate without changing what it says.
Contents
- Core Rules
- Patterns to Eliminate
- Engineering Examples
- Adding Voice
- Output Behavior
- Final Scan Process
Core Rules
- Keep every factual and technical claim. Shorten or restructure without changing meaning.
- Never add a fact, name, number, date, quote, citation, cause, or conclusion that the source does not support.
- Match a provided writing sample's tone, vocabulary, sentence rhythm, and level of formality.
- State the problem directly and include enough context to make the text useful.
- Keep uncertainty when the evidence, intent, or outcome is genuinely uncertain.
- Add personality only when the audience and format call for it. Keep technical, factual, legal, and security text neutral.
- Treat the patterns below as signals, not proof. Rewrite awkward combinations instead of mechanically replacing isolated words.
- Prefer the shortest complete explanation. Do not reduce useful reasoning to a cryptic fragment.
Patterns to Eliminate
Sycophantic Openings and Chatbot Artifacts
Delete empty praise, greetings, offers, and sign-offs:
- "Great question!"
- "Excellent point!"
- "You're absolutely right!"
- "Good catch!"
- "Nice work on this PR!"
- "Of course!" / "Certainly!"
- "I hope this helps!"
- "Let me know if you have questions!"
- "Feel free to reach out!"
- "Happy to help!"
Keep a greeting or sign-off only when the requested format calls for one.
Unsupported Hedging
Remove qualifiers that only soften a supported claim. Keep qualifiers that carry real uncertainty.
Before: "You might want to consider adding validation here." After: "Add validation here."
Before: "Because items[0] may be missing, this could potentially cause issues."
After: "items[0] is undefined for an empty array."
Valid uncertainty: "Not sure if this is intentional, but retries now skip rate-limit errors."
Mechanical AI Vocabulary
Prefer simple words when meaning stays the same:
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.
- 24d ago First seen · 187 lines · 62 tokens per session scan A b704aadad7d1
humanizing-ai-text is a skill published in the GitHub repository andrzejchm/fdb (46 stars, last pushed 12d ago), licensed MIT. It adds 62 tokens to every session and 1,757 once invoked, about $0.0002 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 2026-10-01.
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