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 sgaabdu4/hard-eng --skill writing-artifactsgit clone --depth 1 https://github.com/sgaabdu4/hard-engWrote 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/sgaabdu4/hard-eng/writing-artifacts)<a href="https://agentmods.dev/skills/sgaabdu4/hard-eng/writing-artifacts"><img src="https://agentmods.dev/badge/skills/sgaabdu4/hard-eng/writing-artifacts/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/sgaabdu4/hard-eng/writing-artifacts"><img src="https://agentmods.dev/badge/skills/sgaabdu4/hard-eng/writing-artifacts.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 | $0.00054 | $0.00490 |
| Opus 5 | $0.00027 | $0.00245 |
| Sonnet 5 | $0.00011 | $0.00098 |
| Haiku 4.5 | $0.00005 | $0.00049 |
Grade A, and why
writing-artifacts 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 9d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Artifacts
Brief
- Identify audience, purpose, reader action, format, tone, length, and source constraints.
- If a missing choice would change the result, ask. Otherwise choose a plain, useful default.
- Treat supplied facts, links, code, names, dates, and examples as source truth. Mark unknowns; do not invent them.
- Honor the artifact's requested length. Do not force the chat reply word cap onto a paste-ready deliverable.
Format branches
Medium article
- Open with the reader's problem, promise, or a concrete story. Earn attention quickly.
- State one clear thesis. Give each section one job, with examples or evidence that move it forward.
- Use a useful title, readable headings, specific transitions, and a conclusion that leaves the reader with a decision or next step.
- Remove sales language, generic lessons, fake certainty, and filler introductions.
GitHub issue
- Title = the observable problem or requested outcome.
- Structure = summary + context + steps to reproduce + expected behavior + actual behavior + evidence + scope + acceptance criteria.
- Preserve exact errors, paths, commands, versions, dates, and links. Separate facts from hypotheses.
- Report one coherent problem. Include a proposed fix only when requested or clearly useful.
Pull request
- Structure = what changed + why + user or system impact + proof run + risk or rollout notes.
- Link the issue or decision when supplied. State known gaps and follow-up work without hiding it in prose.
Docs, notes, and copy
- Describe the accepted current state, not the editing history.
- Match the reader's job: explain, decide, perform, or understand. Use headings, examples, and calls to action only when they help.
Final pass
- Check audience, purpose, structure, claims, links, code, dates, length, and requested tone.
- Remove repetition, chatbot filler, inflated claims, unexplained jargon, and process commentary.
- Return the finished artifact first. Add a short note only when the user asks for explanation or a material gap needs attention.
What ships with it
1 file 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.
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.
- 9d ago First seen · 46 lines · 54 tokens per session scan A 4daa552d37b3
writing-artifacts is a skill published in the GitHub repository sgaabdu4/hard-eng (5 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 490 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 2026-08-30.
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