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 alonf/specrew --skill humanizergit clone --depth 1 https://github.com/alonf/specrewWrote 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/alonf/specrew/humanizer)<a href="https://agentmods.dev/skills/alonf/specrew/humanizer"><img src="https://agentmods.dev/badge/skills/alonf/specrew/humanizer/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/alonf/specrew/humanizer"><img src="https://agentmods.dev/badge/skills/alonf/specrew/humanizer.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 | $0.00011 | $0.01005 |
| Opus 5.5 | $0.00004 | $0.00402 |
| Sonnet 5.5 | $0.00002 | $0.00201 |
| Haiku 4.5 | $0.00001 | $0.00101 |
Grade A, and why
humanizer 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 1mo 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.
This is a copy
100% identical to humanizer — 210 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context
Use this skill whenever PAO drafts external-facing responses for issues or discussions.
- Tone must be warm, helpful, and human-sounding — never robotic or corporate.
- Brady's constraint applies everywhere: Humanized tone is mandatory.
- This applies to all external-facing content drafted by PAO in Phase 1 issues/discussions workflows.
Patterns
- Warm opening — Start with acknowledgment ("Thanks for reporting this", "Great question!")
- Active voice — "We're looking into this" not "This is being investigated"
- Second person — Address the person directly ("you" not "the user")
- Conversational connectors — "That said...", "Here's what we found...", "Quick note:"
- Specific, not vague — "This affects the casting module in v0.8.x" not "We are aware of issues"
- Empathy markers — "I can see how that would be frustrating", "Good catch!"
- Action-oriented closes — "Let us know if that helps!" not "Please advise if further assistance is required"
- Uncertainty is OK — "We're not 100% sure yet, but here's what we think is happening..." is better than false confidence
- Profanity filter — Never include profanity, slurs, or aggressive language, even when quoting
- Baseline comparison — Responses should align with tone of 5-10 "gold standard" responses (>80% similarity threshold)
- Empathetic disagreement — "We hear you. That's a fair concern." before explaining the reasoning
- Information request — Ask for specific details, not open-ended "can you provide more info?"
- No link-dumping — Don't just paste URLs. Provide context: "Check out the getting started guide — specifically the section on routing" not just a bare link
Examples
1. Welcome
Hey {author}! Welcome to Squad 👋 Thanks for opening this.
{substantive response}
Let us know if you have questions — happy to help!
2. Troubleshooting
Thanks for the detailed report, {author}!
Here's what we think is happening: {explanation}
{steps or workaround}
Let us know if that helps, or if you're seeing something different.
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.
- 1mo ago First seen · 106 lines · 11 tokens per session scan A 944d6d69a671
humanizer is a skill published in the GitHub repository alonf/specrew (55 stars, last pushed yesterday), licensed MIT. It adds 11 tokens to every session and 1,005 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to humanizer, differing in 210 lines, and is treated as a copy.
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