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/whh110112/human-writing-skillsWrote 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/rules/whh110112/human-writing-skills/human-writing)<a href="https://agentmods.dev/rules/whh110112/human-writing-skills/human-writing"><img src="https://agentmods.dev/badge/rules/whh110112/human-writing-skills/human-writing/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/rules/whh110112/human-writing-skills/human-writing"><img src="https://agentmods.dev/badge/rules/whh110112/human-writing-skills/human-writing.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 | $0.00000 | $0.00157 |
| Opus 5 | $0.00000 | $0.00078 |
| Sonnet 5 | $0.00000 | $0.00031 |
| Haiku 4.5 | $0.00000 | $0.00016 |
Grade A, and why
human-writing 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 6d 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
Use the project's selected writing style and preserve established facts, terminology, speaker identity, relationships, spatial state, props, injuries, unresolved promises, and sources. Do not claim that a detector can prove authorship.
For fiction, let dialogue and action change the scene before explaining their emotion.
For serious writing, preserve numbers, citations, URLs, code, named terms, and claim scope.
Use human-writing-skills lint, stats, verify, or the MCP tools when the task asks
for auditing. For long work, use a confirmed continuity ledger and chunked audit package.
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.
- 6d ago First seen · 15 lines · 0 tokens per session scan A cfa759c839e3
human-writing is a cursor rule published in the GitHub repository whh110112/human-writing-skills (2 stars, last pushed 7d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 157 tokens. 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 2026-09-04.
Other cursor rules, from other repositories
avoid-ai-writing
Audit and rewrite content to remove AI writing patterns ("AI-isms"). Activate whenever editing prose-heavy files (Markdown, documentation, blog posts, READMEs, release notes, emails). Cursor port of the avoid-ai-writing skill v3.33.2. See https://github.com/conorbronsdon/avoid-ai-writing.
jawn
Cursor rule "jawn" from Helicone/helicone, covering helicone jawn controller and tanstack query integration, controller pattern, manager pattern, frontend hooks with tanstack query and type definitions.
lean
Answer densely. Cut filler, keep all technical signal.
Documentation
Professional Documentation Standards for GitHub OSS Projects - Developer, Collaborator, and User Readiness.
task
Task execution rules for Glitch Payment Gateway engineering work — verification gates, plan node, self-improvement loop.
software-factory
Software factory operating rules.