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 claude-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/claude-academy-guide)<a href="https://agentmods.dev/skills/guanyang/open-agent-hub/claude-academy-guide"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/claude-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/claude-academy-guide"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/claude-academy-guide.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 | $0.00250 | $0.01854 |
| Opus 5 | $0.00125 | $0.00927 |
| Sonnet 5 | $0.00050 | $0.00371 |
| Haiku 4.5 | $0.00025 | $0.00185 |
Grade A, and why
claude-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 13d 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.
This is a copy
94% identical to academy-guide — 25 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 151 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.
- 13d ago First seen · 151 lines · 250 tokens per session scan A 1df757c172f3
claude-academy-guide is a skill published in the GitHub repository guanyang/open-agent-hub (967 stars, last pushed yesterday), licensed MIT. It adds 250 tokens to every session and 1,854 once invoked, about $0.0013 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to academy-guide, differing in 25 lines, and is treated as a copy.
Other skills, from other repositories
81-pipecat
Create your Pipecat skill from official documentation, then learn to improve it throughout the chapter.
34-openai-agents-sdk-panaversity-agentfactory-8f59f147
Create your OpenAI Agents SDK skill in one prompt, then learn to improve it throughout the chapter.
35-google-adk-reliable-agents
Create your Google Agent Development Kit skill in one prompt, then learn to improve it throughout the chapter.
36-anthropic-agents-kit-development
Create your Claude Agent SDK skill in one prompt, then learn to improve it throughout the chapter.
book-recommender
A Chinese-language book recommendation and analysis skill that evaluates what books are about, whether they are worth reading, and how to read them.
feynman-write
A research-and-writing workflow based on the Feynman method, where the AI gathers source material and the author decides the article's focus, then explains the ideas through questioning. The final text keeps the author's own examples and voice while adding technical precision.