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 ur-grue/autopunk-media-skills --skill methodology-explainergit clone --depth 1 https://github.com/ur-grue/autopunk-media-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/ur-grue/autopunk-media-skills/methodology-explainer)<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/methodology-explainer"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/methodology-explainer/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/ur-grue/autopunk-media-skills/methodology-explainer"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/methodology-explainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00046 | $0.01448 |
| Opus 5 | $0.00023 | $0.00724 |
| Sonnet 5 | $0.00009 | $0.00290 |
| Haiku 4.5 | $0.00005 | $0.00145 |
Grade A, and why
methodology-explainer 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 10d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Methodology Explainer
What This Skill Does
Writes a plain-language explanation of a data journalism methodology — what data was used, where it came from, how it was processed, and what the analysis found — suitable for publication alongside a data story.
When To Use This Skill
- You have completed a data analysis and need a methodology box or explainer to accompany the published article
- An editor requires a methodology statement for editorial transparency or legal protection
- You are preparing a data story for a publication that requires published methodologies as standard
- You want to write the methodology in language that non-specialist readers can understand, without omitting the detail that expert readers need
What You Need To Provide
Required: A description of the data used (source, time period, scope). The analysis steps you performed (what you calculated, how you grouped or filtered data, any joins or merges with other datasets). The key findings. Any known limitations or caveats in the data or analysis. Optional: How the data was obtained (FOI, open data, licensed); what software or tools were used; whether the data was independently verified; whether any external expert reviewed the methodology.
How the Assistant Approaches This
- Structures the methodology in the order a reader needs it: what data was used, how it was obtained, what was done with it, and what the results mean — followed by honest caveats.
- Writes for two audiences simultaneously: the general reader who wants a short, reassuring summary that the journalism is solid, and the specialist reader who needs enough detail to reproduce or challenge the methodology.
- Balances transparency with accessibility — avoids statistical jargon unless necessary, and always explains it when used.
Output Format
A methodology statement of 300–500 words structured under four headings: Data Sources, How We Analysed It, What We Found, and Caveats and Limitations. Tone: clear, direct, confident but honest. Written in first-person plural ("we obtained," "we analysed") or third-person ("the analysis used"), according to publication style. No jargon unexplained.
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.
- 10d ago First seen · 82 lines · 46 tokens per session scan A 374419176f36
methodology-explainer is a skill published in the GitHub repository ur-grue/autopunk-media-skills (30 stars, last pushed 10d ago), licensed MIT. It adds 46 tokens to every session and 1,448 once invoked, about $0.0002 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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