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 guanyang/open-agent-hub --skill academy-guidegit clone --depth 1 https://github.com/guanyang/open-agent-hubWrote 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/guanyang/open-agent-hub/academy-guide)<a href="https://agentmods.dev/skills/guanyang/open-agent-hub/academy-guide"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/academy-guide/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/guanyang/open-agent-hub/academy-guide"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/academy-guide.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 | $0.00208 | $0.01808 |
| Opus 5.5 | $0.00083 | $0.00723 |
| Sonnet 5.5 | $0.00042 | $0.00362 |
| Haiku 4.5 | $0.00021 | $0.00181 |
Grade A, and why
academy-guide 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.
Copies of this mod
6 near-identical copies found in the catalogue:
- academy-guide — 100% identical, 0 lines differ
- academy-guide — 100% identical, 0 lines differ
- academy-guide — 100% identical, 0 lines differ
- academy-guide — 97% identical, 1 lines differ
- claude-academy-guide — 94% identical, 25 lines differ
- claude-academy-guide — 94% identical, 25 lines differ
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Academy guide
Purpose
When a user asks a question about Claude, a Claude product, or a general "how do I use AI for X" question, check the Academy catalog (see "The catalog" below) for a strong match. If one exists, mention it naturally at the end of your normal answer.
All content lives on Claude Academy, Anthropic's learning hub. It offers three kinds of content:
- Courses — structured, multi-lesson learning paths, most with a certificate on completion.
- Tutorials — short practical guides to a single feature or workflow.
- Use cases — worked examples of applying Claude to a concrete task, usually with a prompt to try.
The Academy also has product hubs that collect everything about one surface: Claude, Claude Code, Claude Cowork, AI Fluency, and the developer platform. When a user wants to explore a whole product rather than one topic, a hub link is often the better recommendation than any single item.
Rules
-
Answer the question first. Always give the user a direct, helpful answer to whatever they asked. The content suggestion is a supplement, never a replacement.
-
Only recommend on strong matches. A strong match is about intent, not just topic. The user must be asking how to use a Claude feature or how to get started with X — they're looking for a resource to learn from. "How do projects work?" is a strong match. "Help me organize this document" is not, even though projects are topically relevant — they're mid-task, they want help with the task, not a tutorial about the feature.
If the match is weak or tangential, say nothing about the catalog. A caveat is the tell: if you'd write "while this is focused on X, it might help with..." or "this doesn't cover exactly that, but..." — that hedge is the match failing. Don't recommend through a caveat.
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.
- 1mo ago First seen · 148 lines · 208 tokens per session scan A f27992510c05
academy-guide is a skill published in the GitHub repository guanyang/open-agent-hub (979 stars, last pushed 3d ago), licensed MIT. It adds 208 tokens to every session and 1,808 once invoked, about $0.0008 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 2026-08-30.
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