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.
git clone --depth 1 https://github.com/ofershap/ai-humanizerWrote 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/commands/ofershap/ai-humanizer/audit)<a href="https://agentmods.dev/commands/ofershap/ai-humanizer/audit"><img src="https://agentmods.dev/badge/commands/ofershap/ai-humanizer/audit/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/commands/ofershap/ai-humanizer/audit"><img src="https://agentmods.dev/badge/commands/ofershap/ai-humanizer/audit.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 | $0.00020 | $0.00357 |
| Opus 5.5 | $0.00008 | $0.00143 |
| Sonnet 5.5 | $0.00004 | $0.00071 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
audit 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 2mo 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
Scan the current project for AI fingerprints that detectors and experienced developers would flag.
Check these file types: README.md, CHANGELOG.md, docs/, *.md, code comments, package.json descriptions, PR templates.
For each file, look for:
- Em dashes (—) used as separators
- Flagged vocabulary: delve, tapestry, leverage, utilize, facilitate, streamline, paramount, pivotal, meticulous, holistic, robust, comprehensive, multifaceted, harness, foster, bolster, seamless, cutting-edge, game-changing, revolutionary, groundbreaking, nuanced, intricate, elevate, empower, unleash
- AI opening/closing cliches: "In today's...", "It's worth noting...", "In summary...", "Happy coding!"
- Narrating code comments: comments that describe what the next line does instead of why
- Over-formatting: bold-label bullets, uniform list lengths, excessive markdown
- Low burstiness: 4+ consecutive sentences of similar length
- AI git metadata: Co-authored-by trailers for AI tools in recent commits
For each finding:
- Show the file and line
- Quote the problematic text
- Suggest a human-sounding replacement
- Rate: high (em dashes, flagged words, git trailers) / medium (cliches, over-formatting) / low (burstiness, minor style)
After the scan, show a summary count by category.
Use the ai-humanizer skill for the full reference of patterns to check.
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.
- 2mo ago First seen · 36 lines · 20 tokens per session scan A 699763cc22af
audit is a command published in the GitHub repository ofershap/ai-humanizer (5 stars, last pushed 8mo ago), licensed MIT. It adds 20 tokens to every session and 357 once invoked, about $0.0001 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 2026-08-31.
audit compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| auditofershap/ai-humanizer | Command | 5 | 8mo ago | MIT | A | 20 | Claude Code |
| deaidbhosbu-dotcom/renwei | Command | 6 | 3mo ago | none | A | 24 | Claude Code |
| deai-fixdbhosbu-dotcom/renwei | Command | 6 | 3mo ago | none | A | 15 | Claude Code |
| deai-scandbhosbu-dotcom/renwei | Command | 6 | 3mo ago | none | A | 20 | Claude Code |
| accent-dialpetar-djukic/writing-skills | Command | 5 | today | MIT | A | 1 | GitHub Copilot |
| audit-referencespetar-djukic/writing-skills | Command | 5 | today | MIT | A | 1 | GitHub Copilot |
| critic-applypetar-djukic/writing-skills | Command | 5 | today | MIT | A | 1 | GitHub Copilot |