skills/research-subscription/SKILL.md
# Research Subscription Skill Summary This skill handles **scheduled and recurring tasks** like literature digests, delayed reports, and reminders. ## Key Usage Activate when users request: - Scheduled literature updates or paper tracking - Delayed reports (e.g., tomorrow morning) - Recurring push notifications - Time-based reminders ## Core Action Call `scientify_cron_job` with: - **`action`**: "upsert" (create/update), "list", or "remove" - **`topic`**: for research subscriptions (e.g., "
npx skillsauth add lamm-mit/scienceclaw skills/research-subscriptionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill handles scheduled and recurring tasks like literature digests, delayed reports, and reminders.
Activate when users request:
Call scientify_cron_job with:
action: "upsert" (create/update), "list", or "remove"topic: for research subscriptions (e.g., "LLM alignment")message: for plain reminders onlyUse formats like:
daily 08:00 Asia/Shanghaiweekly mon 09:30 Asia/Shanghaievery 6hat 2mOptionally specify channel ("feishu", "telegram", "slack", etc.) and to (recipient ID). Default routing applies if unset.
For recurring research jobs:
Confirm: job status, effective schedule with timezone, delivery target, and next action options.
🐍Scientify
tools
Onboard and manage Paperclip AI for research-paper knowledge and agent orchestration
development
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
testing
Generate a structured scientific PDF report from a JSON description. Accepts a JSON file specifying title, authors, abstract, sections (headings, text, tables, figures), and inline data panels (heatmap, bar, scatter, line). Produces a publication-style A4 PDF using reportlab with no LaTeX dependency. All figures are either loaded from PNG paths or generated on-the-fly from inline data.
development
Execute arbitrary Python code and return stdout. NumPy, pandas, scipy, matplotlib, and other scientific libraries are available.