Research External

/research-external <focus> [options]

question: "What kind of information do you need?"
header: "Type"
options:
  - label: "How to use a library/package"
    description: "API docs, examples, patterns"
  - label: "Best practices for a task"
    description: "Recommended approaches, comparisons"
  - label: "General topic research"
    description: "Comprehensive multi-source search"
  - label: "Compare options/alternatives"
    description: "Which tool/library/approach is best"

question: "What specifically do you want to research?"
header: "Topic"
options: []  # Free text input

question: "Which package registry?"
header: "Registry"
options:
  - label: "npm (JavaScript/TypeScript)"
    description: "Node.js packages"
  - label: "PyPI (Python)"
    description: "Python packages"
  - label: "crates.io (Rust)"
    description: "Rust crates"
  - label: "Go modules"
    description: "Go packages"

question: "How thorough should the research be?"
header: "Depth"
options:
  - label: "Quick answer"
    description: "Just the essentials"
  - label: "Thorough research"
    description: "Multiple sources, examples, edge cases"

question: "What should I produce?"
header: "Output"
options:
  - label: "Summary in chat"
    description: "Tell me what you found"
  - label: "Research document"
    description: "Write to thoughts/shared/research/"
  - label: "Handoff for implementation"
    description: "Prepare context for coding"

Based on your answers, I'll research:

**Focus:** library
**Topic:** "Prisma ORM connection pooling"
**Library:** prisma (npm)
**Depth:** thorough
**Output:** doc

Proceed? [Yes / Adjust settings]

FOCUS=$1           # library | best-practices | general
TOPIC="..."        # from --topic
DEPTH="shallow"    # from --depth (default: shallow)
OUTPUT="doc"       # from --output (default: doc)
LIBRARY="..."      # from --library (optional)
REGISTRY="npm"     # from --registry (default: npm)

# Semantic search in package
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/nia_docs.py \
  --package "$LIBRARY" \
  --registry "$REGISTRY" \
  --query "$TOPIC" \
  --limit 10)

# If thorough depth, also grep for specific patterns
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/nia_docs.py \
  --package "$LIBRARY" \
  --grep "$TOPIC")

# Supplement with official docs if URL known
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/firecrawl_scrape.py \
  --url "https://docs.example.com/api/$TOPIC" \
  --format markdown)

# AI-synthesized research (sonar-pro)
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --research "$TOPIC best practices 2024 2025")

# If comparing alternatives
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --reason "$TOPIC vs alternatives - which to choose?")

# Chain-of-thought for complex decisions
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --reason "$TOPIC tradeoffs and considerations 2025")

# Deep comprehensive research
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --deep "$TOPIC comprehensive guide 2025")

# Recent developments
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --search "$TOPIC latest developments" \
  --recency month --max-results 5)

(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/nia_docs.py \
  --search "$TOPIC")

(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
  --research "$TOPIC")

# Scrape relevant documentation pages found in perplexity results
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/firecrawl_scrape.py \
  --url "$FOUND_DOC_URL" \
  --format markdown)

---
date: {ISO timestamp}
type: external-research
topic: "{topic}"
focus: {focus}
sources: [nia, perplexity, firecrawl]
status: complete
---

# Research: {Topic}

## Summary
{2-3 sentence summary of findings}

## Key Findings

### Library Documentation
{From nia-docs - API references, usage patterns}

### Best Practices (2024-2025)
{From perplexity - recommended approaches}

### Code Examples

## Recommendations
- {Recommendation 1}
- {Recommendation 2}

## Pitfalls to Avoid
- {Pitfall 1}
- {Pitfall 2}

## Alternatives Considered
| Option | Pros | Cons |
|--------|------|------|
| {Option 1} | ... | ... |

## Sources
- [{Source 1}]({url1})
- [{Source 2}]({url2})

---
type: research-handoff
ts: {ISO timestamp}
topic: "{topic}"
focus: {focus}
status: complete
---

goal: Research {topic} for implementation planning
sources_used: [nia, perplexity, firecrawl]

findings:
  key_concepts:
    - {concept1}
    - {concept2}

  code_examples:
    - pattern: "{pattern name}"
      code: |
        // example code

  best_practices:
    - {practice1}
    - {practice2}

  pitfalls:
    - {pitfall1}

recommendations:
  - {rec1}
  - {rec2}

sources:
  - title: "{Source 1}"
    url: "{url1}"
    type: {documentation|article|reference}

for_plan_agent: |
  Based on research, the recommended approach is:
  1. {Step 1}
  2. {Step 2}
  Key libraries: {lib1}, {lib2}
  Avoid: {pitfall1}

Research Complete

Topic: {topic}
Focus: {focus}
Output: {path to file}

Key findings:
- {Finding 1}
- {Finding 2}
- {Finding 3}

Sources: {N} sources cited

{If handoff output:}
Ready for plan-agent to continue.

   tool_status:
     nia: success
     perplexity: failed (rate limited)
     firecrawl: skipped

   ## Gaps
   - Perplexity unavailable - best practices section limited to nia results

/research-external library --topic "dependency injection" --library fastapi --registry py_pi

/research-external best-practices --topic "error handling in Python async" --depth thorough

/research-external general --topic "OAuth2 PKCE flow implementation" --depth thorough --output handoff

/research-external library --topic "useEffect cleanup" --library react