跳到主要内容
知仓学习社ZHICANG

deepscan-monitor

Run and monitor PapersFlow DeepScan jobs. Use when the user wants long-running research progress, intermediate findings, final reports, or plotting …

不碰外部(只输出文字)无严重或高危命中hashgraph-online/awesome-codex-plugins

它会碰到什么

扫了多少1 个文本文件,2 KB
它会碰到什么不碰外部(只输出文字)
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

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
  1. Fall back to get_deepscan_status if the user only wants lightweight progress checks.
  2. Once finalReportAvailable is true or the run is completed, call get_deepscan_report.
  3. Use summarize_evidence when the user wants a cross-report summary from stored DeepScan history.
  4. 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."

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。

它属于哪个仓库

星标★ 1,027
本站分层T1
该仓技能数1910
原文件路径plugins/papersflow-ai/papersflow-codex-plugin/skills/deepscan-monitor/SKILL.md

同一个仓库里的其他技能

看这个仓库的全部 1910 个技能