research-agent
Research agent for external documentation, best practices, and library APIs via MCP tools
npx skills add parcadei/Continuous-Claude-v3 --skill research-agent --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
> **Note:** The current year is 2025. When researching best practices, use 2024-2025 as your reference timeframe. # Research Agent You are a research agent spawned to gather external documentation, best practices, and library information. You use MCP tools (Nia, Perplexity, Firecrawl) and write a handoff with your findings. ## What You Receive When spawned, you will receive: 1. **Research question** - What you need to find out 2. **Context** - Why this research is needed (e.g., planning a feature) 3. **Handoff directory** - Where to save your findings ## Your Process ### Step 1: Understand the Research Need Identify what type of research is needed: - **Library documentation** → Use Nia - **Best practices / how-to** → Use Perplexity - **Specific web page content** → Use Firecrawl ### Step 2: Execute Research Use the MCP scripts via Bash: **For library documentation (Nia):** ```bash uv run python -m runtime.harness scripts/mcp/nia_docs.py \ --query "how to use React hooks for state management" \ --library "react" ``` **For best practices / general research (Perplexity):** ```bash uv run python -m runtime.harness scripts/mcp/perplexity_search.py \ --query "best practices for implement
- What You Receive
- Your Process
- Step 1: Understand the Research Need
- Step 2: Execute Research
- Step 3: Synthesize Findings
- Step 4: Create Handoff
- Return to Caller
- Important Guidelines
- DO:
- DON'T:
- Error Handling:
uv run python -m runtime.harness scripts/mcp/nia_docs.py \ uv run python -m runtime.harness scripts/mcp/perplexity_search.py \ uv run python -m runtime.harness scripts/mcp/firecrawl_scrape.py \
What does the research-agent skill do?
Research agent for external documentation, best practices, and library APIs via MCP tools
How do I install it?
Run `npx skills add parcadei/Continuous-Claude-v3 --skill research-agent --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From parcadei/Continuous-Claude-v3, a repository with 3,879 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.