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 commands/kkry486/ai-learn-plugin/learngit clone --depth 1 https://github.com/kkry486/ai-learn-pluginWhat 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 | $0.00055 | $0.00204 |
| Opus 5 | $0.00028 | $0.00102 |
| Sonnet 5 | $0.00011 | $0.00041 |
| Haiku 4.5 | $0.00006 | $0.00020 |
Grade A, and why
learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
启动 AI 辅助学习系统，激活 ai-learn Agent。
用户想学习的主题是：$ARGUMENTS
如果用户没有提供主题，请友好地询问用户想学习什么内容。 如果用户提供了主题，直接调用 ai-learn Agent 开始五步学习工作流。
在执行工作流之前，首先检查 knowledge_store 目录是否有 store.py，如果没有，
告知用户需要先安装依赖：pip install chromadb sqlite3
然后继续执行工作流（第一次使用知识库为空，步骤4跳过关联检索即可）。
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.
- 2d ago First seen · 16 lines · 55 tokens per session scan A 5cc4cf59f750
learn is a command published in the GitHub repository kkry486/ai-learn-plugin (5 stars, last pushed 2mo ago), licensed MIT. It adds 55 tokens to every session and 204 once invoked, about $0.0003 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.