ResearchMonitor
Monitors research topics for new papers, conferences, and journals.
Best use case
ResearchMonitor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Monitors research topics for new papers, conferences, and journals.
Teams using ResearchMonitor should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/researchassistant/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ResearchMonitor Compares
| Feature / Agent | ResearchMonitor | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Monitors research topics for new papers, conferences, and journals.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# ResearchMonitor
This skill helps you keep the user updated on their specific research field.
## Workflow
1. **Check Configuration**:
- Read `research_config.json` in this directory to find the user's research topics and last checked date.
- If the file doesn't exist or topics are empty, ask the user what research topics they are interested in and save them using `scripts/daily_briefing.py --add-topic "topic"`.
2. **Daily Check**:
- Get the current date.
- Compare with `last_checked` in `research_config.json`.
- If already checked today, do nothing unless explicitly asked.
3. **Perform Search**:
- For each topic, use `search_web` to look for:
- "new research papers [topic] [current month/year]"
- "upcoming conferences [topic] [current year]"
- "new journal issues [topic] [current month/year]"
- Check specialized platforms like arXiv, IEEE Xplore, Google Scholar (via web search), or X (Twitter) if relevant.
4. **Filter & Analyze**:
- For each potential item found, use `scripts/daily_briefing.py --check-seen "URL or Unique Title"`.
- If it returns "true", SKIP IT.
- Compare found items with what might have been seen yesterday (this requires some memory or just checking if the publication date is very recent, e.g., last 24-48 hours).
- **CRITICAL**: If there is *nothing significantly new* (no new major papers, no new conference announcements), **DO NOT BOTHER THE USER**.
5. **Report**:
- If new items are found, compile a brief markdown report.
- Include:
- **Title**: News/Paper Title
- **Source**: URL/Journal Name
- **Summary**: 1-sentence summary of why it's relevant.
- Present this to the user.
- Mark the items as seen using `scripts/daily_briefing.py --mark-seen "URL or Unique Title"`.
- Update the `last_checked` date using `scripts/daily_briefing.py --update-date`.
## Scripts
- `python scripts/daily_briefing.py --add-topic "topic"`: Adds a new research topic.
- `python scripts/daily_briefing.py --list-topics`: Lists current topics.
- `python scripts/daily_briefing.py --update-date`: Updates the last checked timestamp to now.
- `python scripts/daily_briefing.py --check-seen "ID"`: Checks if an item ID (URL/Title) is already in memory.
- `python scripts/daily_briefing.py --mark-seen "ID"`: Marks an item ID as seen.Related Skills
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