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 AgentComputerAI/torch --skill wikipediagit clone --depth 1 https://github.com/AgentComputerAI/torchWrote 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/agentcomputerai/torch/wikipedia)<a href="https://agentmods.dev/skills/agentcomputerai/torch/wikipedia"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/wikipedia/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/agentcomputerai/torch/wikipedia"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/wikipedia.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 | $0.00102 | $0.02091 |
| Opus 5.5 | $0.00041 | $0.00836 |
| Sonnet 5.5 | $0.00020 | $0.00418 |
| Haiku 4.5 | $0.00010 | $0.00209 |
Grade A, and why
wikipedia 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.
- **Phase 0 (curl)**: Full article HTML returned in ~165 KB, no challenge, no 403. Gate A passed. How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wikipedia (wikipedia.org)
Wikipedia is the easiest possible scrape target: plain server-rendered HTML, generous robots.txt, no bot detection, no rate limiting for reasonable use, and an official API if you want to skip HTML entirely. The only real trap is the 2023+ heading-wrapper div — scrapers that look for
h2as a direct child of.mw-parser-outputwill silently return zero sections.
Detection
| Signal | Value |
|---|---|
| CDN | Wikimedia / Varnish (x-cache, x-varnish) |
| Framework | MediaWiki (server-rendered PHP) |
| Anti-bot | None |
| Auth | Not required for reads |
| robots.txt | Permissive for well-behaved bots; send a descriptive UA |
| JS required | No — full article in initial HTML |
Architecture
Every article lives at https://<lang>.wikipedia.org/wiki/<Title> and is fully server-rendered. The article body is inside:
#mw-content-text > .mw-parser-output
Direct children of .mw-parser-output include <p>, <ul>, <ol>, tables, figures, and — crucially — <div class="mw-heading mw-heading2/3/4"> wrappers around each section heading. Inside that wrapper is the real <h2>/<h3>/<h4> plus an edit-section link. There is no .mw-headline span anymore on modern output; the heading text is just the direct text of the h2/h3/h4.
Reference list: ol.references > li, with the citation text inside .reference-text.
Categories: #mw-normal-catlinks ul li a.
Strategy used
- Phase 0 (curl): Full article HTML returned in ~165 KB, no challenge, no 403. Gate A passed.
- Phase 1: Skipped — no framework JSON to extract; HTML is the source of truth.
- Phase 2: Skipped — no browser needed.
Total time to extract a full article: < 1 second.
Alternative: official APIs (use these for structured data)
If you don't need HTML-level fidelity, skip scraping entirely:
- REST API —
https://en.wikipedia.org/api/rest_v1/page/summary/<Title>returns title, extract, thumbnail, description. - REST API (HTML) —
https://en.wikipedia.org/api/rest_v1/page/html/<Title>returns clean Parsoid HTML (easier to parse than the skinned article page). - Action API —
https://en.wikipedia.org/w/api.php?action=parse&page=<Title>&format=json&prop=sections|text|links|categoriesreturns everything as JSON. - Dumps — for bulk work, use
dumps.wikimedia.orginstead of crawling.
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 · 171 lines · 102 tokens per session scan A 2403bb808aa6
wikipedia is a skill published in the GitHub repository AgentComputerAI/torch (5 stars, last pushed 6mo ago), licensed MIT. It adds 102 tokens to every session and 2,091 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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