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/gullitmiranda/.cursor/learngit clone --depth 1 https://github.com/gullitmiranda/.cursorWrote 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/commands/gullitmiranda/.cursor/learn)<a href="https://agentmods.dev/commands/gullitmiranda/.cursor/learn"><img src="https://agentmods.dev/badge/commands/gullitmiranda/.cursor/learn.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.00276 |
| Opus 5 | $0.00008 | $0.00138 |
| Sonnet 5 | $0.00003 | $0.00055 |
| Haiku 4.5 | $0.00002 | $0.00028 |
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.
What it actually says
/learn
Persist "learned" instructions in a tool-agnostic way.
Canonical behavior lives in the learn skill:
skills/learn/SKILL.md
Usage examples:
/learn "In this repo, we use pnpm."/learn "Only for me in this repo: run tests first"(project-local)/learn "For all my projects: ask before commits"(user)/learn "scope=user: only push when explicitly requested"(explicit scope)/learn "Applies to backend/: prefer pytest fixtures"(contextual)
When this command is used:
- Apply the
learnskill workflow. - Default scope to
projectfor repo conventions, but preferscope=userwhen the text is clearly a personal preference about the assistant's behavior (not a project convention).- Examples that should infer
scope=user(even without an explicit prefix):- "Always respect when I'm told to use a git worktree."
- "Only push when explicitly requested."
- "Ask before committing."
- PT-BR equivalents: "sempre ...", "nunca ...", "nao faça ...", when addressed to the assistant's behavior.
- Examples that should infer
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 · 30 lines · 15 tokens per session scan A 4ca4283d3872
learn is a command published in the GitHub repository gullitmiranda/.cursor (2 stars, last pushed 6mo ago), licensed MIT. It adds 15 tokens to every session and 276 once invoked, about $0.0001 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
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
neo-review
Get Neo's code review with semantic matching against past findings in memory. Use on a diff or module before merge, especially where earlier mistakes in this codebase are likely to recur. Skip for formatting, lint-catchable issues, and single-line changes.