sport-science-review_skill

Overview

This skill is an automated sports science intelligence engine that aggregates 55+ global sources into a single daily report. It filters noise, translates content to Chinese (or other target languages), deduplicates against local history, and syncs the final report to Feishu and optionally Notion. Designed for coaches, researchers, and product teams who need concise, evidence-based summaries daily.

How this skill works

The agent fetches peer‑reviewed papers from PubMed, crawls RSS feeds from expert blogs and podcasts, and monitors industry sources. It applies a four‑layer keyword filter and a trusted‑source whitelist to surface high‑value items, then deduplicates against local history. Content is auto‑translated via Google Translate API, formatted into a Markdown report, and pushed to Feishu Cloud (with an optional Notion sync).

When to use it

• Daily monitoring of new sports science research and industry updates.
• Preparing quick evidence summaries for team briefings or athlete interventions.
• Keeping product or R&D teams informed about wearable tech and measurement advances.
• Automating multilingual dissemination of research highlights to Chinese teams.
• Archiving feeds and research snapshots for audit or literature review workflows.

Best practices

• Run the report during low‑traffic hours and set --days to capture the desired lookback window.
• Maintain Feishu app credentials and optional Notion tokens securely via environment variables.
• Tune the keyword lists and trusted source whitelist in config.py to match your domain focus.
• Rotate or archive processed_history.json periodically if you want repeated coverage of older items.
• Use --no-history sparingly to force reprocessing when investigating missed items or QA.

Example use cases

• A sportscience lead generates a daily digest for coaches highlighting recent training physiology papers.
• A product manager tracks wearable device firmware and validation studies to inform feature roadmaps.
• A clinician compiles translated research summaries for non‑English speaking stakeholders.
• An R&D team archives source snapshots for later systematic review or meta‑analysis.
• A content team sources credible story leads from expert blogs and peer‑reviewed journals.