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/raja21068/AutoResearchWrote 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/agents/raja21068/autoresearch/article-writing-skill)<a href="https://agentmods.dev/agents/raja21068/autoresearch/article-writing-skill"><img src="https://agentmods.dev/badge/agents/raja21068/autoresearch/article-writing-skill.svg" alt="Measured on agentmods" 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 | $0.00057 | $0.00649 |
| Opus 5 | $0.00028 | $0.00324 |
| Sonnet 5 | $0.00011 | $0.00130 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
article-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 7d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Article Writing
Write long-form content that sounds like a real person or brand, not generic AI output.
When to Activate
- drafting blog posts, essays, launch posts, guides, tutorials, or newsletter issues
- turning notes, transcripts, or research into polished articles
- matching an existing founder, operator, or brand voice from examples
- tightening structure, pacing, and evidence in already-written long-form copy
Core Rules
- Lead with the concrete thing: example, output, anecdote, number, screenshot description, or code block.
- Explain after the example, not before.
- Prefer short, direct sentences over padded ones.
- Use specific numbers when available and sourced.
- Never invent biographical facts, company metrics, or customer evidence.
Voice Capture Workflow
If the user wants a specific voice, collect one or more of:
- published articles
- newsletters
- X / LinkedIn posts
- docs or memos
- a short style guide
Then extract:
- sentence length and rhythm
- whether the voice is formal, conversational, or sharp
- favored rhetorical devices such as parentheses, lists, fragments, or questions
- tolerance for humor, opinion, and contrarian framing
- formatting habits such as headers, bullets, code blocks, and pull quotes
If no voice references are given, default to a direct, operator-style voice: concrete, practical, and low on hype.
Banned Patterns
Delete and rewrite any of these:
- generic openings like "In today's rapidly evolving landscape"
- filler transitions such as "Moreover" and "Furthermore"
- hype phrases like "game-changer", "cutting-edge", or "revolutionary"
- vague claims without evidence
- biography or credibility claims not backed by provided context
Writing Process
- Clarify the audience and purpose.
- Build a skeletal outline with one purpose per section.
- Start each section with evidence, example, or scene.
- Expand only where the next sentence earns its place.
- Remove anything that sounds templated or self-congratulatory.
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.
- 7d ago First seen · 86 lines · 57 tokens per session scan A 6ab082c7850e
article-writing is an agent published in the GitHub repository raja21068/AutoResearch (2 stars, last pushed 3mo ago), licensed MIT. It adds 57 tokens to every session and 649 once invoked, about $0.0003 per session on Opus 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.
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