External research workflow for docs, web, APIs - NOT codebase exploration
npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill research-external
Research external sources (documentation, web, APIs) for libraries, best practices, and general topics.
> Note: The current year is 2025. When researching best practices, use 2024-2025 as your reference timeframe.
/research-external <focus> [options]
If the user types just /research-external with no or partial arguments, guide them through this question flow. Use AskUserQuestion for each phase.
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"
Mapping:
question: "What specifically do you want to research?"
header: "Topic"
options: [] # Free text input
Examples of good answers:
If user selected library focus:
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"
Then ask for specific library name if not already provided.
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"
Mapping:
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"
Mapping:
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 | Primary Tool | Purpose |
|-------|--------------|---------|
| library | nia-docs | API docs, usage patterns, code examples |
| best-practices | perplexity-search | Recommended approaches, patterns, comparisons |
| general | All MCP tools | Comprehensive multi-source research |
| Option | Values | Description |
|--------|--------|-------------|
| --topic | "string" | Required. The topic/library/concept to research |
| --depth | shallow, thorough | Search depth (default: shallow) |
| --output | handoff, doc | Output format (default: doc) |
| --library | "name" | For library focus: specific package name |
| --registry | npm, py_pi, crates, go_modules | For library focus: package registry |
Extract from user input:
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)
libraryPrimary tool: nia-docs - Find API documentation, usage patterns, code examples.
# 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)
Thorough depth additions:
best-practicesPrimary tool: perplexity-search - Find recommended approaches, patterns, anti-patterns.
# 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?")
Thorough depth additions:
# 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)
generalUse ALL available MCP tools - comprehensive multi-source research.
Step 2a: Library documentation (nia-docs)
(cd $CLAUDE_OPC_DIR && uv run python -m runtime.harness scripts/mcp/nia_docs.py \
--search "$TOPIC")
Step 2b: Web research (perplexity)
(cd $CLAUDE_OPC_DIR && uv run python scripts/mcp/perplexity_search.py \
--research "$TOPIC")
Step 2c: Specific documentation (firecrawl)
# 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)
Thorough depth additions:
Combine results from all sources:
doc (default)Write to: thoughts/shared/research/YYYY-MM-DD-{topic-slug}.md
---
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
// Working examples found
## 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})
handoffWrite to: thoughts/shared/handoffs/{session}/research-{topic-slug}.yaml
---
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.
If an MCP tool fails (API key missing, rate limited, etc.):
tool_status:
nia: success
perplexity: failed (rate limited)
firecrawl: skipped
complete - All requested tools succeededpartial - Some tools failed, findings still usefulfailed - No useful results obtained ## 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
| After Research | Use Skill | For |
|----------------|-----------|-----|
| --output handoff | plan-agent | Create implementation plan |
| Code examples found | implement_task | Direct implementation |
| Architecture decision | create_plan | Detailed planning |
| Library comparison | Present to user | Decision making |
NIA_API_KEY or nia server in mcp_config.jsonPERPLEXITY_API_KEY in environment or ~/.claude/.envFIRECRAWL_API_KEY and firecrawl server in mcp_config.jsonresearch-codebase or scout for thatComprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
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Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
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Take parcadei/research-external from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
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