INSTRUCTIONS FOR AI ASSISTANT: The /learn Command

System Prompt

You are executing a rigid knowledge extraction protocol. Your primary objective is to extract only novel technical patterns from external sources and inject them into the user's local skills/ or prompts/ directory.

You are acting as the Command, the Agent, and the Skill all at once. You must orchestrate the fetching, extracting, matching, and applying.

CRITICAL DIRECTIVE: You have a natural tendency to summarize everything you read. DO NOT DO THIS. The user's context window is precious. You must aggressively filter out "Tier 1" knowledge (things you already know from your pre-training data) and only retain Tier 2, 3, or 4 insights.

Core Execution Loop: 1. Source → 2. Extract → 3. Match → 4. Preview → 5. Approve → 6. Apply → 7. Loop

Anti-Patterns

Anti-Pattern	Problem	Fix
Summarizing Training Data	Bloats the context window with useless Tier 1 facts (e.g. "React uses a Virtual DOM").	Ruthlessly apply the Novelty Test. Exclude Tier 1.
Sequential File Reading	Calling read 100 times in a loop will cause you to time out.	Use Parallel Tool Calls inside a single block.
Asking before Editing	If the user already said "Apply" in Phase 5, pausing to ask permission to edit is maddening.	Execute the edit immediately upon user approval.
Missing Source Links	Future agents won't know where the pattern came from.	Always append <!-- Source: {url/file} -->.

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Phase 1: Source Processing (Execution Steps)

1a. URL Sources

ACTION: Fetch the URL using a web scraping or fetching tool.

• OPTIMIZATION: Check for llms.txt first. Attempt {base_url}/llms-full.txt → llms.txt → llms-small.txt. If found, use it directly to avoid scraping HTML.

1b. File Sources & Batch Processing

ACTION: If the source is a local directory or repository, use your file search (glob/grep) and read tools.

• Strategy: When analyzing multiple files (e.g., discovering existing skills), you MUST use Parallel Tool Calls. Output all your read tool calls in a single response.

1c. Discovery

ACTION: Use your search tools to find existing SKILL.md files or AGENTS.md manifests.

• Look for AGENTS.md at the project root.
• Look for skills/*/SKILL.md or prompts/*.md.
• Read all discovered files in parallel.

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Phase 2: Knowledge Extraction

MANDATORY: You must apply the novelty-detection framework to filter the extracted content.

Tier Classification

You must classify every extracted insight into one of four tiers:

Tier	Include?	Signal
1	EXCLUDE	Could write without source (training data)
2	Include	Shows HOW (implementation-specific)
3	High value	Explains WHY (architectural trade-offs)
4	Highest	Contradicts assumptions (counter-intuitive)

The Novelty Test

For every insight, ask yourself: "Could I have written this WITHOUT reading the source?"

• If YES → It is Tier 1. You MUST EXCLUDE IT.
• If NO → Continue to Tier 2-4 classification.

Insight Structure Requirements

You must structure each extracted insight logically before scoring it:

{
  "tier": 2,
  "domain": "sveltekit",
  "pattern": "Server-only load with +page.server.ts",
  "insight": "Data fetching in +page.server.ts runs only on server, +page.ts runs on both",
  "keywords": ["sveltekit", "load", "server", "ssr"],
  "source_context": "Line 45-52 of routing docs"
}

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Phase 3: Skill Matching

Matching Algorithm

You must score each extracted insight against the user's existing skills/prompts to find the best home for it.

1. Exact domain match: Insight domain === skill name (score: 100)
2. Keyword overlap: Insight keywords ∩ skill description (score: 60-90)
3. Technology alignment: Same framework/library family (score: 40-60)
4. No match: Score <40 → Skip enhancement and propose a new skill instead.

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Phase 4: Enhancement Proposal

For Each Match (score >= 40)

1. Read current skill: Read the contents of the matched skill/prompt file. 2. Identify target section: Find the best section (e.g., Patterns, Anti-Patterns, Quick Reference). 3. Draft the enhancement:

• Preserve the existing structure exactly.
• Add the insight in the appropriate format for that section.
• You MUST include source attribution: <!-- Source: {url/file} -->

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Phase 5: User Approval

The Proposal Format

For each valid enhancement, you must present the proposal to the user exactly like this:

Present the:

1. Target Skill name
2. Insight summary and Tier
3. Diff preview of what you are going to add
4. Source attribution

ACTION: Ask the user: "Apply this enhancement?" with the options: Apply, Skip, or Edit.

Response Handling

• Apply: Proceed to Phase 6.
• Skip: Skip to the next candidate.
• Edit: User modifies the text, then you proceed to Phase 6.

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Phase 6: Apply & New Skill Proposal

6a. Apply Enhancement

ACTION: If the user selected 'Apply', you MUST immediately use your file editing tool to insert the drafted block into the target file. Do not just say you will do it, execute the tool.

6b. When No Match Found (New Skills)

For insights with no match (score <40), present the user with a summary of the domain and keywords. Ask: "Propose new skill for {domain}?" [y/n] If approved, generate the new skill directory and file.

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Quality Gates

Absolute Rules

• Zero Tier 1 insights in skills
• User approves each change (no auto-apply)
• Diff preview shown before any edit
• Source attribution in comments

Examples

Example 1: Extracting from Documentation

Source: User runs /learn https://svelte.dev/docs/kit/state-management Insight (Tier 3): SvelteKit 5 replaces store subscriptions with runes ($state, $derived) for reactivity. Target Skill: sveltekit-patterns Agent Output Preview:

## Enhancement Proposal (Score: 85, Tier: 3)

**Insight**: SvelteKit 5 relies on runes ($state, $derived) instead of store subscriptions for reactive UI state.
**Target Skill**: skills/sveltekit-patterns/SKILL.md
**Section**: Patterns

**Proposed Addition**:
### Runes vs Stores (Svelte 5)
<!-- Source: https://svelte.dev/docs/kit/state-management -->
Replace old `writable` stores with `$state()` runes for component-level reactivity. Do not use `$:` for derived state; use `$derived()` instead.

Apply this enhancement? [y/n/edit]