egocentric_view_to_structured_log
Converts first-person XR headset video into a structured experiment timeline log. Extracts timestamped events (action, object, location, result) via VLM or action recognition, outputs Markdown or JSON for downstream analysis, reporting, protocol compliance audit, or ELN attachment.
npx skills add BioTender-max/awesome-bio-agent-skills --skill egocentric_view_to_structured_log --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Egocentric View to Structured Log ## Overview `egocentric_view_to_structured_log` transforms raw first-person XR headset footage into a machine-readable experiment timeline. It processes the egocentric video stream frame-by-frame (or at configurable intervals), applies VLM or action-recognition models to infer what the operator did — pipetting, vortexing, adding reagent, loading centrifuge, labeling tube — and emits a structured log with timestamp, action type, object(s) involved, spatial location, and optional result or observation. The output is Markdown (human-readable timeline) or JSON (for programmatic consumption), suitable for ELN attachment, protocol compliance cross-reference, `generate_scientific_method_section` input, or audit trail documentation in the LabOS "from video to paper" pipeline. ## When to Use This Skill Use this skill when any of the following conditions are present: - **Experiment timeline documentation**: A researcher needs a chronological record of what was done during an experiment — "at 14:23, added buffer to tube A1; at 14:25, vortexed; at 14:30, loaded centrifuge" — without manual note-taking. - **ELN or Benchling attachment**: An electronic lab not
- Overview
- When to Use This Skill
- Core Capabilities
- 1. Egocentric Video Processing
- 2. Action & Object Recognition
- 3. Location & Context Enrichment
- 4. Structured Log Schema
- 5. Output Formats & Export Options
- 6. Integration with Downstream Skills
- Usage Examples
- Example 1 — Post-Recording Full Log (JSON)
- Example 2 — Markdown for ELN Attachment
- Example 3 — Real-Time Streaming Log (NDJSON)
- Integration Notes
What does the egocentric_view_to_structured_log skill do?
Converts first-person XR headset video into a structured experiment timeline log. Extracts timestamped events (action, object, location, result) via VLM or action recognition, outputs Markdown or JSON for downstream analysis, reporting, protocol compliance audit, or ELN attachment.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill egocentric_view_to_structured_log --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.