deepscan-monitor

name	deepscan-monitor
description	Run and monitor PapersFlow DeepScan jobs. Use when the user wants long-running research progress, intermediate findings, final reports, or plotting from a completed run.

DeepScan Monitor

Use this skill when the user wants Claude to manage a longer-running PapersFlow research workflow instead of a single search call.

Workflow

1. Use run_deepscan to start the job.
2. Immediately tell the user that the run is asynchronous.
3. Poll with get_deepscan_live_snapshot for the best live view of:
   • progress
   • status message
   • checkpoint state
   • top papers
   • partial summary
   • key findings
4. Fall back to get_deepscan_status if the user only wants lightweight progress checks.
5. Once finalReportAvailable is true or the run is completed, call get_deepscan_report.
6. Use summarize_evidence when the user wants a cross-report summary from stored DeepScan history.
7. Use run_python_plot only after you have stable report data worth plotting.

Important Behavior

• Do not imply the MCP server will push completion notifications into Claude automatically.
• Poll deliberately and explain that the run is being checked.
• Prefer get_deepscan_live_snapshot over get_deepscan_status when the user wants richer live information.
• If a report is not ready yet, say that clearly and keep the next action obvious.

Progress Update Style

When a run is still active, summarize:

• current status
• progress percentage
• current stage or status message
• any checkpoint question
• notable live papers
• key findings if available

Keep updates brief unless the user asks for more detail.

Plotting Guidance

Use run_python_plot only for meaningful visualizations after you have stable report outputs, for example:

• papers by year
• citation distribution
• venue distribution
• grouped comparison across a small number of finished runs

Do not generate plots for sparse or obviously low-quality data without saying so.

Examples

• User asks: "Run a DeepScan on evaluation benchmarks for agentic retrieval systems and keep me posted."
• User asks: "Check how my DeepScan is progressing and tell me the key findings so far."
• User asks: "The run is finished, summarize the final report and plot papers by year."
• User asks: "Summarize the evidence from my recent DeepScan reports on protein structure prediction."