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 h4vzz/awesome-ai-agent-skills --skill technical-writinggit clone --depth 1 https://github.com/h4vzz/awesome-ai-agent-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/skills/h4vzz/awesome-ai-agent-skills/technical-writing)<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/technical-writing"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/technical-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/skills/h4vzz/awesome-ai-agent-skills/technical-writing"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/technical-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 | $0.00035 | $0.01574 |
| Opus 5.5 | $0.00014 | $0.00630 |
| Sonnet 5.5 | $0.00007 | $0.00315 |
| Haiku 4.5 | $0.00003 | $0.00157 |
Grade A, and why
technical-writing scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> curl -X POST https://api.example.com/api/v1/webhooks \ This is a copy
91% identical to technical-writing — 2 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Technical Writing
This skill enables an AI agent to produce high-quality technical documentation across a range of formats — API references, user guides, getting-started tutorials, changelogs, architecture decision records, and more. The agent analyzes the target audience, structures information logically, applies consistent formatting standards, and ensures every document is accurate, scannable, and actionable.
Workflow
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Identify Document Type and Audience Determine which type of document is needed (API reference, tutorial, user guide, changelog, architecture doc) and who will read it (beginner developers, experienced engineers, end users, stakeholders). Adjust vocabulary, depth, and assumed prerequisites accordingly. A tutorial for beginners should explain every step; an API reference for senior engineers should be terse and precise.
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Gather Source Material Collect all relevant inputs: source code, existing documentation, design documents, user stories, API schemas (OpenAPI/Swagger), commit histories, or stakeholder interviews. Identify the authoritative source for each piece of information to ensure accuracy. Note any gaps that need clarification.
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Design the Document Structure Create an outline following the conventions of the document type. API references use a consistent per-endpoint template. Tutorials follow a step-by-step progression. Architecture docs follow a decision-record format (context, decision, consequences). Plan where code examples, tables, and callout boxes will appear.
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Write the Content Draft the document using clear, direct language. Prefer active voice and short sentences. Lead each section with the most important information. Include complete, runnable code examples that readers can copy and execute. Use consistent terminology and define acronyms on first use. Format according to the chosen standard (Markdown, reStructuredText, AsciiDoc).
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Add Navigation and Cross-References Insert a table of contents for long documents, anchor links between related sections, and links to prerequisite or follow-up documentation. Add "Next steps" sections at the end of tutorials.
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 · 132 lines · 35 tokens per session scan A 0ff553fd1282
technical-writing is a skill published in the GitHub repository h4vzz/awesome-ai-agent-skills (36 stars, last pushed 22d ago), licensed MIT. It adds 35 tokens to every session and 1,574 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 91% identical to technical-writing, differing in 2 lines, and is treated as a copy.
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