learn

Research a topic and save structured knowledge to ~/.claude/learnings/ for future session use.

Input

Topic string from $ARGUMENTS. Examples:

• TanStack Router
• Go concurrency patterns
• Redis Streams

Process

1. Generate Slug

Convert topic to filesystem-safe slug: lowercase, replace non-alphanumeric with hyphens, collapse consecutive hyphens, trim.

• "TanStack Router" -> tanstack-router
• "Go concurrency patterns" -> go-concurrency-patterns

2. Check Existing Knowledge

ls ~/.claude/learnings/<slug>.md 2>/dev/null

If the file exists, read its frontmatter. Ask the user: Update (merge new findings), Replace (full rewrite), or Cancel?

3. Ensure Directory

mkdir -p ~/.claude/learnings

4. Research

Use available tools based on topic category. Adapt if MCP tools are unavailable.

Library/Framework (e.g., "TanStack Router", "Express.js"):

1. Context7 resolve-library-id + query-docs for API surface
2. GitHub grep for real-world usage patterns
3. WebSearch for version-specific changes, migration notes, known issues

Concept/Pattern (e.g., "CQRS", "Go concurrency patterns"):

1. WebSearch for authoritative sources
2. WebFetch key references
3. GitHub grep for real implementations

Tool/CLI (e.g., "Docker Compose", "jq"):

1. WebSearch for official docs
2. WebFetch documentation pages
3. GitHub grep for config/usage examples

Language Feature (e.g., "Go generics", "TypeScript decorators"):

1. WebSearch for official specs/proposals
2. Context7 for language docs if available
3. GitHub grep for adoption patterns

5. Save Knowledge File

Write to ~/.claude/learnings/<slug>.md using this format:

---
topic: "<Original Topic Name>"
slug: "<slug>"
category: "<library|concept|tool|language-feature>"
created: "<YYYY-MM-DD>"
last_verified: "<YYYY-MM-DD>"
confidence: "<high|medium|low>"
tags: [<relevant, tags>]
sources_count: <N>
---

# <Topic Name>

## TL;DR
<2-4 sentences: what it is, key capabilities, primary use case.>

## Core APIs / Concepts

### <Name>
- **Signature/Usage**: `<code>`
- **Purpose**: <one line>
- **Example**:
```<lang>
<minimal working example>

<Name>

...

Patterns & Recipes

<Common usage patterns as self-contained code blocks. Annotate sparingly -- only non-obvious details.>

Gotchas

• <Issue>: <What happens + fix/workaround>
• <Issue>: <What happens + fix/workaround>

Quick Reference

<Compact table or list: key APIs, flags, commands. Optimized for fast lookup.>

Sources

1. <Title>
2. <Title>

### 6. Knowledge Graph Indexing (Optional)

If `mcp__memory__create_entities` is available, create an entity:

```json
{
  "name": "<Topic Name>",
  "entityType": "learning",
  "observations": [
    "Saved to ~/.claude/learnings/<slug>.md",
    "Category: <category>",
    "Tags: <tag1>, <tag2>"
  ]
}

7. Confirm

Tell the user: file path, topic name, source count, and that /recall <topic> retrieves it.

Quality Rules

• Accuracy over breadth. Fewer verified facts > many uncertain ones.
• Code examples must be correct and minimal. Mark untested code with // untested.
• Set confidence high only when multiple authoritative sources agree.
• Include version numbers for libraries. Note if info may become outdated quickly.

Self-Maintenance

When reading any ~/.claude/learnings/ file during normal work:

1. If last_verified is >90 days old, treat content as potentially stale.
2. If you find inaccuracies during use, silently update the file: fix content, bump last_verified, adjust confidence. No user confirmation needed.
3. Do NOT rewrite files for style. Only update with verified corrections.