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 agentmods add skills/agentskill-sh/ags/learnnpx skills add agentskill-sh/ags --skill learngit clone --depth 1 https://github.com/agentskill-sh/agsWhat 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 | $0.00115 | $0.03363 |
| Opus 5 | $0.00057 | $0.01682 |
| Sonnet 5 | $0.00023 | $0.00673 |
| Haiku 4.5 | $0.00012 | $0.00336 |
Grade A, and why
learn 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 3d 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 — 349 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn — Find & Install Agent Skills
Search 100,000+ skills from agentskill.sh. Delegates all operations to the ags CLI via npx @agentskill.sh/cli. The CLI is auto-downloaded by npx on first use.
All commands below use npx @agentskill.sh/cli with --json for structured output.
Platform Interaction
Different agent platforms have different tools for user interaction. Adapt your approach based on what's available.
If AskUserQuestion tool is available (Claude Code, Cursor, etc.):
- Use
AskUserQuestionfor all user selections (creates interactive buttons) - Include header, question, and labeled options with descriptions
- Max 4 options per question (tool limit)
If AskUserQuestion tool is NOT available (OpenHands, Codex, Aider, etc.):
- Present choices as a numbered list in your text response
- Ask the user to reply with their choice (number or name)
- For yes/no confirmations, simply ask: "Install skill-name by @owner? (yes/no)"
Detection: Before your first interaction prompt, check if AskUserQuestion is in your available tools. Cache this detection for the session.
Commands
This skill registers a single command, /learn, with subcommands for all operations.
/learn <query> — Search for Skills
When the user runs /learn followed by a search query, search for matching skills.
Steps:
- Run via Bash:
npx @agentskill.sh/cli search "<query>" --json --limit 5 - Parse the JSON response (has
resultsarray withslug,name,owner,description,installCount,securityScore,contentQualityScore) - Display results using a clean markdown table format:
## Skills matching "<query>" | # | Skill | Author | Installs | Security | |---|-------|--------|----------|----------| | 1 | **<name>** | @<owner> | <installCount> | <securityScore>/100 | ... **Descriptions:** 1. **<name>**: <description (first 80 chars)> ... - Present interactive selection (see Platform Interaction section):
- If
AskUserQuestionis available: create options from search results (max 4), label = skill name, description = "@, installs, Security: /100", header = "Install", question = "Which skill would you like to install?" - If not available: present a numbered list and ask the user to reply with their choice
- If
- If user selects a skill, proceed to the Install Flow below
- If user selects "Other" or asks to do something else, accommodate
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.
- 3d ago First seen · 349 lines · 115 tokens per session scan A e6b59a320ace
learn is a skill published in the GitHub repository agentskill-sh/ags (35 stars, last pushed 3mo ago), licensed MIT. It adds 115 tokens to every session and 3,363 once invoked, about $0.0006 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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