Learn

---
name: learn
description: "Research any topic online and create learning guides. Use when user asks to 'learn about', 'research topic', 'create learning guide', 'build knowledge base', or 'study subject'."
version: 1.0.0
argument-hint: "[topic] [--depth=brief|medium|deep]"
---

# learn

Research any topic by gathering online resources and creating a comprehensive learning guide with RAG-optimized indexes.

## Input

Arguments: `<topic> [--depth=brief|medium|deep]`

- **topic**: Subject to research (required)
- **--depth**: Source gathering depth
  - `brief`: 10 sources (quick overview)
  - `medium`: 20 sources (default, balanced)
  - `deep`: 40 sources (comprehensive)

## Research Methodology

Based on best practices from:
- Anthropic's Context Engineering
- DeepLearning.AI Tool Use Patterns
- Anara's AI Literature Reviews

### 1. Progressive Query Architecture

Use funnel approach to avoid noise from long query lists:

**Broad Phase** (landscape mapping):
```
"{topic} overview introduction"
"{topic} documentation official"
```

**Focused Phase** (core content):
```
"{topic} best practices"
"{topic} examples tutorial"
"{topic} site:stackoverflow.com"
```

**Deep Phase** (advanced, if depth=deep):
```
"{topic} advanced techniques"
"{topic} pitfalls mistakes avoid"
"{topic} 2025 2026 latest"
```

### 2. Source Quality Scoring

Multi-dimensional evaluation (max score: 100):

| Factor | Weight | Max | Criteria |
|--------|--------|-----|----------|
| Authority | 3x | 30 | Official docs (10), recognized expert (8), established site (6), blog (4), random (2) |
| Recency | 2x | 20 | <6mo (10), <1yr (8), <2yr (6), <3yr (4), older (2) |
| Depth | 2x | 20 | Comprehensive (10), detailed (8), overview (6), superficial (4), fragment (2) |
| Examples | 2x | 20 | Multiple code examples (10), one example (6), no examples (2) |
| Uniqueness | 1x | 10 | Unique perspective (10), some overlap (6), duplicate content (2) |

**Selection threshold**: Top N sources by score (N = depth target)

### 3. Just-In-Time Retrieval

Don't pre-load all content (causes context rot):

1. **Collect URLs first** via WebSearch
2. **Score based on metadata** (title, description, URL)
3. **Fetch only selected sources** via WebFetch
4. **Extract summaries** (not full content)

### 4. Content Extraction Guidelines

For each source, extract:

```json
{
  "url": "https://...",
  "title": "Article Title",
  "qualityScore": 85,
  "scores": {
    "authority": 9,
    "recency": 8,
    "depth": 7,
    "examples": 9,
    "uniqueness": 6
  },
  "keyInsights": [
    "Concise insight 1",
    "Concise insight 2"
  ],
  "codeExamples": [
    {
      "language": "javascript",
      "description": "Basic usage pattern"
    }
  ],
  "extractedAt": "2026-02-05T12:00:00Z"
}
```

**Copyright compliance**: Summaries and insights only, never verbatim paragraphs.

## Output Structure

### Topic Guide Template

Create `agent-knowledge/{slug}.md`:

```markdown
# Learning Guide: {Topic}

**Generated**: {date}
**Sources**: {count} resources analyzed
**Depth**: {brief|medium|deep}

## Prerequisites

What you should know before diving in:
- Prerequisite 1
- Prerequisite 2

## TL;DR

Essential points in 3-5 bullets:
- Key point 1
- Key point 2
- Key point 3

## Core Concepts

### {Concept 1}

{Synthesized explanation from multiple sources}

**Key insight**: {Most important takeaway}

### {Concept 2}

{Synthesized explanation}

## Code Examples

### Basic Example

```{language}
// Description of what this demonstrates
{code}
```

### Advanced Pattern

```{language}
{code}
```

## Common Pitfalls

| Pitfall | Why It Happens | How to Avoid |
|---------|---------------|--------------|
| Issue 1 | Root cause | Prevention strategy |

## Best Practices

Synthesized from {n} sources:

1. **Practice 1**: Explanation
2. **Practice 2**: Explanation

## Further Reading

| Resource | Type | Why Recommended |
|----------|------|-----------------|
| [Title]({url}) | Official Docs | Authoritative reference |
| [Title]({url}) | Tutorial | Step-by-step guide |

---

*Generated by /learn from {count} sources.*
*See `resources/{slug}-sources.json` for full source metadata.*
```

### Master Index Template

Create/update `agent-knowledge/CLAUDE.md`:

```markdown
# Agent Knowledge Base

> Learning guides created by /learn. Reference these when answering questions about listed topics.

## Available Topics

| Topic | File | Sources | Depth | Created |
|-------|------|---------|-------|---------|
| {Topic 1} | {slug1}.md | {n} | medium | 2026-02-05 |
| {Topic 2} | {slug2}.md | {n} | deep | 2026-02-04 |

## Trigger Phrases

Use this knowledge when user asks about:
- "How does {topic1} work?" → {slug1}.md
- "Explain {topic1}" → {slug1}.md
- "{Topic2} best practices" → {slug2}.md

## Quick Lookup

| Keyword | Guide |
|---------|-------|
| recursion | recursion.md |
| hooks, react | react-hooks.md |

## How to Use

1. Check if user question matches a topic
2. Read the relevant guide file
3. Answer based on synthesized knowledge
4. Cite the guide if user asks for sources
```

Copy to `agent-knowledge/AGENTS.md` for OpenCode/Codex.

### Sources Metadata

Create `agent-knowledge/resources/{slug}-sources.json`:

```json
{
  "topic": "{original topic}",
  "slug": "{slug}",
  "generated": "2026-02-05T12:00:00Z",
  "depth": "medium",
  "totalSources": 20,
  "sources": [
    {
      "url": "https://...",
      "title": "...",
      "qualityScore": 85,
      "scores": {
        "authority": 9,
        "recency": 8,
        "depth": 7,
        "examples": 9,
        "uniqueness": 6
      },
      "keyInsights": ["..."]
    }
  ]
}
```

## Self-Evaluation Checklist

Before finalizing, rate output (1-10):

| Metric | Question | Target |
|--------|----------|--------|
| Coverage | Does guide cover main aspects? | ≥7 |
| Diversity | Are sources from diverse types? | ≥6 |
| Examples | Are code examples practical? | ≥7 |
| Accuracy | Confidence in content accuracy? | ≥8 |

**Flag gaps**: Note any important subtopics not covered.

## Enhancement Integration

If enhance=true, invoke after guide creation:

```javascript
// Enhance the topic guide for RAG
Skill({ name: 'enhance:enhance-docs', args: `agent-knowledge/${slug}.md --ai` });

// Enhance the master index
Skill({ name: 'enhance:enhance-prompts', args: 'agent-knowledge/CLAUDE.md' });
```

## Output Format

Return structured JSON between markers:

```
=== LEARN_RESULT ===
{
  "topic": "recursion",
  "slug": "recursion",
  "depth": "medium",
  "guideFile": "agent-knowledge/recursion.md",
  "sourcesFile": "agent-knowledge/resources/recursion-sources.json",
  "sourceCount": 20,
  "sourceBreakdown": {
    "officialDocs": 4,
    "tutorials": 5,
    "stackOverflow": 3,
    "blogPosts": 5,
    "github": 3
  },
  "selfEvaluation": {
    "coverage": 8,
    "diversity": 7,
    "examples": 9,
    "accuracy": 8,
    "gaps": ["tail recursion optimization not covered"]
  },
  "enhanced": true,
  "indexUpdated": true
}
=== END_RESULT ===
```

## Error Handling

| Error | Action |
|-------|--------|
| WebSearch fails | Retry with simpler query |
| WebFetch timeout | Skip source, note in metadata |
| <minSources found | Warn user, proceed with available |
| Enhancement fails | Skip, note in output |
| Index doesn't exist | Create new index |

## Token Budget

Estimated token usage by phase:

| Phase | Tokens | Notes |
|-------|--------|-------|
| WebSearch queries | ~2,000 | 5-8 queries |
| Source scoring | ~1,000 | Metadata only |
| WebFetch extraction | ~40,000 | 20 sources × 2,000 avg |
| Synthesis | ~10,000 | Guide generation |
| Enhancement | ~5,000 | Two skill calls |
| **Total** | ~60,000 | Within opus budget |

## Integration

This skill is invoked by:
- `learn-agent` for `/learn` command
- Potentially other research-oriented agents