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Pop Knowledge Lookup

ASecurity

Queries cached external documentation and blog content for authoritative, up-to-date information. Sources include Claude Code docs, engineering blog, and configured knowledge bases with 24-hour TTL caching. Use when you need current information about Claude Code features, hooks, or best practices. Do NOT use for general coding questions - rely on training knowledge or web search instead.

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  • Added September 2, 2026
ai-agentspythongobashsqldocumentation

Works with

  • claude code
  • cli
  • mcp

Security analysis

A100/100

Scanned September 2, 2026

npx -y skills add majiayu000/claude-skill-registry --skill pop-knowledge-lookup --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: pop-knowledge-lookup
description: "Queries cached external documentation and blog content for authoritative, up-to-date information. Sources include Claude Code docs, engineering blog, and configured knowledge bases with 24-hour TTL caching. Use when you need current information about Claude Code features, hooks, or best practices. Do NOT use for general coding questions - rely on training knowledge or web search instead."
---

# Knowledge Lookup

## Overview

Query cached external documentation and blog content to get fresh context for development tasks. Knowledge sources are synced on session start and cached for 24 hours.

**Core principle:** Get authoritative, up-to-date information from official sources.

**Trigger:** When you need current information about Claude Code, best practices, or configured documentation sources.

## When to Use

Invoke this skill when:

- User asks about Claude Code features or best practices
- You need to reference official documentation
- Answering questions about hooks, commands, or Claude Code architecture
- Looking for examples from the engineering blog

## Available Knowledge Sources

Default sources (synced automatically):

1. **anthropic-engineering** - Claude Code Engineering Blog
2. **claude-code-docs-overview** - Claude Code Documentation Overview
3. **claude-code-docs-hooks** - Claude Code Hooks Reference

## Lookup Process

### Step 1: List Available Knowledge

Use the **Read tool** to check what knowledge is available:

```
Read: ~/.claude/config/knowledge/sources.json
```

### Step 2: Check Cache Freshness

Use bash for SQLite queries (no native equivalent):

```bash
sqlite3 ~/.claude/config/knowledge/cache.db \
  "SELECT source_id, fetched_at, expires_at, status FROM knowledge_cache"
```

### Step 3: Read Specific Content

Use the **Read tool** to read cached content:

```
Read: ~/.claude/config/knowledge/content/anthropic-engineering.md
Read: ~/.claude/config/knowledge/content/claude-code-docs-overview.md
```

### Step 4: Search Across Sources

Use the **Grep tool** to search across all cached content:

```
Grep: pattern="hooks", path="~/.claude/config/knowledge/content/"
Grep: pattern="MCP", path="~/.claude/config/knowledge/content/"
```

### Step 5: Semantic Search (If Available)

When embeddings are initialized, use semantic similarity for better results:

```python
# Check if semantic search is available
from popkit_shared.utils.embedding_store import EmbeddingStore
from popkit_shared.utils.voyage_client import is_available

store = EmbeddingStore()
if is_available() and store.count("knowledge") > 0:
    # Semantic search available
    from popkit_shared.utils.voyage_client import embed_query

    query_embedding = embed_query("how do hooks work")
    results = store.search(
        query_embedding,
        source_type="knowledge",
        top_k=5,
        min_similarity=0.7
    )

    for result in results:
        print(f"[{result.similarity:.2f}] {result.record.source_id}")
        print(f"  {result.record.content[:100]}...")
```

**Hybrid Search Strategy:**

1. Try semantic search first (if embeddings available)
2. Fall back to Grep for keyword matching
3. Combine results with weighted scoring:
   - Semantic score: 70% weight
   - Keyword match: 30% weight

**Initialize Embeddings:**

```bash
python hooks/utils/embedding_init.py --force
```

## Response Format

When providing information from knowledge sources:

```markdown
## Knowledge Reference

**Source:** [Source Name]
**Fetched:** [Timestamp]
**Relevance:** [Why this is relevant to the query]

### Key Information

[Relevant excerpt or summary from cached knowledge]

---

_From cached knowledge source: [source_id]_
_Last updated: [fetched_at]_
```

## Example Queries

### Query: "How do hooks work in Claude Code?"

1. Use the **Read tool** to read the hooks documentation:

   ```
   Read: ~/.claude/config/knowledge/content/claude-code-docs-hooks.md
   ```

2. Extract relevant sections
3. Provide answer with source attribution

### Query: "What are best practices for Claude Code?"

1. Use the **Read tool** to read the engineering blog:

   ```
   Read: ~/.claude/config/knowledge/content/anthropic-engineering.md
   ```

2. Look for best practices content
3. Summarize with examples

### Query: "Is there something about X in the docs?"

1. Use the **Grep tool** to search all sources:

   ```
   Grep: pattern="X", path="~/.claude/config/knowledge/content/"
   ```

2. If found, use **Read tool** to get the full context
3. If not found, inform user and suggest they check directly

## Handling Stale or Missing Data

If knowledge is stale or missing:

```markdown
**Note:** The cached knowledge for [source] is [stale/missing].

Last fetched: [date] (expired [time] ago)

Would you like me to:

1. Refresh the knowledge sources? (`/popkit:knowledge refresh`)
2. Provide what I have from my training data?
3. Search the web for current information?
```

## Related

- `/popkit:knowledge` command - Manage knowledge sources
- `knowledge-sync.py` hook - Automatic session start sync
- Session start hook - Triggers knowledge sync with TTL check

Attribution

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