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/noah-sheldon/ai-dev-kit/learngit clone --depth 1 https://github.com/noah-sheldon/ai-dev-kitWhat 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 | $0.00009 | $0.00066 |
| Opus 5 | $0.00005 | $0.00033 |
| Sonnet 5 | $0.00002 | $0.00013 |
| Haiku 4.5 | $0.00001 | $0.00007 |
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
Learn
Extract reusable lessons from recent work.
Delegate
Apply the documentation-lookup skill.
Notes
- Keep the workflow bounded and explicit.
- Keep responses short and direct.
- Prefer the maintained skill surface over duplicated prompt logic.
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 · 18 lines · 9 tokens per session scan A c6050c41fab9
learn is a command published in the GitHub repository noah-sheldon/ai-dev-kit (13 stars, last pushed 4mo ago), licensed MIT. It adds 9 tokens to every session and 66 once invoked, about $0.0000 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.
Other commands, from other repositories
audit-quiz-coverage
Find quiz coverage gaps from recent guide/CHANGELOG/CC-releases changes and propose new questions.
ship
Ship it. Pre-flight validation, CI check, and PR creation. Run after /review.
context-hub-setup
Use when setting up new development environment or troubleshooting MCP connectivity. Configures Context Hub dependencies including Forgetful MCP server and plugin prerequisites.
memory-list
DEPRECATED: Use Serena listmemories instead. Lists recent memories from Forgetful with optional project filtering.
retro
Execute the canonical workflow: .agent/workflows/retro.md.
dashboard
Launch the learning dashboard web UI to view and edit plans, progress, and spaced repetition data.