DeepScan Monitor
SkillMonitoring & opsRun and monitor PapersFlow DeepScan jobs. Use when the user wants long-running research progress, intermediate findings, final reports, or plotting from a completed run.
Use DeepScan Monitor in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add DeepScan Monitor and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use the DeepScan Monitor skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/papersflow-ai/papersflow-codex-plugin/skills/deepscan-monitor/SKILL.md and read by ahel’s review.
Use this skill when the user wants Claude to manage a longer-running PapersFlow research workflow instead of a single search call.
Workflow
- Use
run_deepscanto start the job. - Immediately tell the user that the run is asynchronous.
- Poll with
get_deepscan_live_snapshotfor the best live view of:- progress
- status message
- checkpoint state
- top papers
- partial summary
- key findings
- Fall back to
get_deepscan_statusif the user only wants lightweight progress checks. - Once
finalReportAvailableis true or the run is completed, callget_deepscan_report. - Use
summarize_evidencewhen the user wants a cross-report summary from stored DeepScan history. - Use
run_python_plotonly 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_snapshotoverget_deepscan_statuswhen 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."
Signals
- GitHub stars
- 1k
- Forks
- 316
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
deepscan-monitor- Source
- github.com/hashgraph-online/awesome-codex-plugins
github.com/hashgraph-online/awesome-codex-plugins
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