Data Research
Structured research pipeline: search sources, extract structured data, archive raw, deduplicate, update canonical trackers, backlink entities.
Contract
One skill for any email-to-structured-data pipeline. The only differences between tracking investor updates, expenses, and company metrics are the search queries, extraction schemas, and tracker page format. All three use the same 7-phase pipeline with parameterized recipes.
When to Use
- User wants to track structured data from email, web, or API sources
- User says "research", "track", "extract from email", "build a tracker"
- User mentions investor updates, donations, company metrics, filings
- User wants to set up recurring data collection (with cron recipe)
Phases
Phase 1: Define Research Recipe
Infer the research target from conversation context, recent brain activity, active
tasks (ops/tasks.md), and memory files. If the request is ambiguous, present the
most likely interpretation based on what the user has been working on. Only ask for
clarification if context is genuinely insufficient. Options:
- Pick a built-in recipe: investor-updates, expense-tracker, company-updates
- D…
