#1 trial priority · skillsdirectory / Coding & Development
Research Collector
- Fit
- 55 / 100
- Trust
- Verified source
- Setup
- MCP ready
- Before run
- 0 checks
Top risk
No community evaluationAgentStaffer users have not submitted a review yet.
Full readiness snapshotCandidate summary and risk context stay available here.
Use when the user wants to collect research material for an article or topic by gathering YouTube videos and web articles into a NotebookLM notebook, then running analysis queries and saving results as markdown. Best for "收集素材"、"给我找这个话题的相关视频和文章"、"整理成 NotebookLM 分析" type requests. Combines yt-dlp YouTube search, NotebookLM `nlm` CLI research, and markdown re...
Top risk
No community evaluation: AgentStaffer users have not submitted a review yet.
Trial task Run a small code review trial
- Input
- Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
- Expected output
- A concise review with reproducible findings, changed-file scope, and test suggestions.
Permissions & setup
- Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
- MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
Promotion gates
- Clear Install path reviewed
- Clear Trust evidence reviewed
Guardrails
- Install asks for production credentials or broad write access.
- Source or package cannot be verified from profile evidence.
Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.