Gather sources and extract fields into canonical tracker pages.
npx skills add https://github.com/ltdrew/Agent-brain-2 --skill data-research-ltdrew
Please help me install this Agent Skill. Skill: data-research Source: https://github.com/ltdrew/Agent-brain-2/tree/main/skills/data-research Command: npx skills add https://github.com/ltdrew/Agent-brain-2 --skill data-research-ltdrew
This Skill enables end-to-end structured data research, from source gathering to canonical tracker updates, reducing manual effort and errors.
Create or customize a YAML recipe at ~/.gbrain/recipes/{name}.yaml and run the data-research pipeline to populate a tracker page.
High-intent search queries and answers about installing and using this skill.
To extract structured data from emails into a tracker, you define a YAML recipe specifying sources and extraction schemas. The pipeline searches emails, extracts fields deterministically, and updates a canonical tracker page with deduplicated entries.
A YAML recipe for structured data research is a configuration file stored at ~/.gbrain/recipes/. It specifies data sources, classification rules, and deterministic extraction schemas needed to consistently gather information and populate tracker pages.
Yes, you can extract company metrics from web sources and APIs using deterministic extraction schemas. The pipeline applies your defined classification rules and regex patterns to gather data, archive raw inputs, and update running totals in trackers.
No, structured data research eliminates manual formatting of investor updates. By applying YAML recipes to emails, web sources, and APIs, the pipeline automatically extracts fields, deduplicates entries, and updates canonical tracker pages with backlinks.
The best way to build an expense tracker from multiple sources is using YAML recipes to define extraction schemas. The pipeline gathers data from emails, web, and APIs, archives raw inputs for auditability, and updates a standard tracker format.
Deterministic extraction schemas require predefined YAML recipes and consistent field structures. If source data from emails or APIs varies significantly from the regex classification rules, the canonical tracker updates may miss or incorrectly map the extracted fields.
ThrookieExtract API patterns from captured traffic or HAR files into OpenAPI specifications and structured pattern files.
ngochuy13Convert research inputs into structured, deduplicated tracker entries with raw-source archiving.
GYF0311Generate structured, deduplicated tracker data from research inputs with provenance.
NinatuziExtract structured data from emails and web pages into canonical tracker pages.
