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 HelloThisWorld/agent-skill-verification-template --skill glossarygit clone --depth 1 https://github.com/HelloThisWorld/agent-skill-verification-templateWrote 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/hellothisworld/agent-skill-verification-template/glossary)<a href="https://agentmods.dev/skills/hellothisworld/agent-skill-verification-template/glossary"><img src="https://agentmods.dev/badge/skills/hellothisworld/agent-skill-verification-template/glossary/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/hellothisworld/agent-skill-verification-template/glossary"><img src="https://agentmods.dev/badge/skills/hellothisworld/agent-skill-verification-template/glossary.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 | $0.00051 | $0.00820 |
| Opus 5.5 | $0.00020 | $0.00328 |
| Sonnet 5.5 | $0.00010 | $0.00164 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
glossary 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 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.
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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Glossary (Wikipedia)
A Claude-style skill that answers glossary <term> requests by looking the
term up on English Wikipedia and returning a definition rendered as a web
page, where every factual claim is backed by a file:line citation into the
fetched article. It is built to be verified like a production component — see
skill-contract.json for the machine-readable contract
and verification-rules.md for how outputs are graded.
When to use
Use this skill for requests such as glossary Mexico or glossary Switzerland.
The term after glossary is looked up; the skill produces a concise,
source-grounded definition and a self-contained HTML page for it.
Tools
| Tool | Purpose |
|---|---|
wikipedia_search |
Search the offline Wikipedia snapshot cache. Returns {title, file, line, text} matches, best article first. |
wikipedia_fetch |
Read a snapshot and return its structured article data plus the citable "lede" line. |
Contract rule: wikipedia_search must be used before wikipedia_fetch.
Offline-first design
Like the rest of this template, the default eval runs fully offline and
deterministically. npm run glossary:build-cache fetches each term once from
English Wikipedia (MediaWiki action API) and writes a citable snapshot to
fixtures/wikipedia/<term>.html. Each snapshot embeds a machine-readable
glossary-data JSON block and a lede line that contains the exact query
term verbatim, so citations stay valid even when Wikipedia's canonical title
or opening phrasing differs from the query. After the cache exists, no network
is required to run or verify the skill.
Procedure
- Parse the term from the
glossary <term>request. - Use
wikipedia_searchto locate the best-matching snapshot. - Use
wikipedia_fetchto read the snapshot and confirm the citable line. - Produce a structured answer whose claim cites that
file:line. - If no snapshot matches the term, return
insufficient_evidencewith an emptyclaimsarray. Never invent a definition or a citation.
What ships with it
3 files 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.
- 1mo ago First seen · 76 lines · 51 tokens per session scan A dbfeed6152cd
glossary is a skill published in the GitHub repository HelloThisWorld/agent-skill-verification-template (1 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 820 once invoked, about $0.0002 per session on Opus 5.5. 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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