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 hanamizuki/solopreneur --skill humanlygit clone --depth 1 https://github.com/hanamizuki/solopreneurWrote 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/hanamizuki/solopreneur/humanly)<a href="https://agentmods.dev/skills/hanamizuki/solopreneur/humanly"><img src="https://agentmods.dev/badge/skills/hanamizuki/solopreneur/humanly/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/hanamizuki/solopreneur/humanly"><img src="https://agentmods.dev/badge/skills/hanamizuki/solopreneur/humanly.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 | $0.00113 | $0.03225 |
| Opus 5.5 | $0.00045 | $0.01290 |
| Sonnet 5.5 | $0.00023 | $0.00645 |
| Haiku 4.5 | $0.00011 | $0.00323 |
Grade A, and why
humanly 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 20d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Humanly — AI Writing Pattern Removal
Remove signs of AI-generated writing. Based on Wikipedia's "Signs of AI writing" and the avoid-ai-writing skill.
Core principle: If you wouldn't say it, don't write it. Write like a smart friend talking.
Order of operations: protect the facts, then strip the AI patterns, then add voice. In that order. A sentence with a point of view that broke a fact is worse than a boring sentence that is correct. And never invent a number, a source, or the author's memories to fill a hole you just made — leave a placeholder and hand it back. See references/protected-list.md.
Mode Detection
| Mode | Trigger | Behavior |
|---|---|---|
| prewrite | Before writing; other skills reference this skill | Read references/generated/prewrite-{lang}.md, internalize, do not run the pipeline |
| rewrite | "rewrite", "clean up", "fix", "去 AI 味", "潤稿", "幫我改" | Full pipeline + rewrite; output 4 sections |
| review | "review", "audit", "scan", "check", "檢查" | Same pipeline but flag-only; output 2 sections (Issues found / Assessment) |
Prewrite Mode
When invoked before writing:
- Detect target language from context
- Read the corresponding generated prewrite file (path relative to this SKILL.md):
- 中文 →
references/generated/prewrite-zh.md - English →
references/generated/prewrite-en.md
- 中文 →
- Internalize the principles and examples, then proceed with the writing task
The prewrite file already bundles the core principles, the "examples teach shape, not license to fabricate" rule, the highest-frequency patterns with before/after examples, the Tier 1 word table (plus banned sentence patterns and the Taiwan localization rules for zh), and a one-line index of every pattern. Do NOT additionally load the full patterns file — it is for rewrite / review mode.
The zh bundle carries the mainland→Taiwan vocabulary and full-width punctuation rules on purpose: the model's Chinese training data is mostly simplified, so it reaches for 視頻 / 質量 / half-width commas while writing. Catching that only in rewrite mode is catching it too late.
What ships with it
12 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.
- evals/benchmark.md 18 KB
- evals/run-eval.md 4.8 KB
- references/context-profiles.md 4.8 KB
- references/generated/prewrite-en.md 23 KB
- references/generated/prewrite-zh.md 35 KB
- references/patterns-en.md 42 KB
- references/patterns-zh.md 55 KB
- references/protected-list.md 9.9 KB
- references/taiwan-localization.md 6.8 KB
- references/word-table-en.md 7.1 KB
- references/word-table-zh.md 6.1 KB
- scripts/build-prewrite.py 13 KB runs code
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.
- 20d ago First seen · 241 lines · 113 tokens per session scan A f24549a591f0
humanly is a skill published in the GitHub repository hanamizuki/solopreneur (154 stars, last pushed 4d ago), licensed MIT. It adds 113 tokens to every session and 3,225 once invoked, about $0.0005 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 2026-09-27.
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