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deepscan-monitor深度扫描监视器

Agent Skill

deepscan-monitor 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

7,393

周安装

302

GitHub Stars

公开资料未说明

下载量

2,368
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:deepscan-monitor(深度扫描监视器)
来源仓库:https://github.com/papersareflowing/deepscan-monitor
安装命令:
openclaw skills install deepscan-monitor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install deepscan-monitor

简介

监控 PapersFlow DeepScan 长期研究作业的运行状态。

  • 提供进展查询、中间结果下载与最终报告获取功能。deepscan-monitor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 支持合作绘图与可视化成果展示,便于团队协作跟进。
  • 作业耗时较长,建议设定合理等待时间再重复查询。
  • 安装后通过命令启动监控,实时跟踪任务执行情况。

SKILL.md

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

  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."

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

93.01%
按下载量换算2,202

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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