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Data Research Pipeline

Search email and web sources, extract structured data into deduplicated tracker pages in your brain

Repository
garrytan/gbrain
Stars
31,447
Licence
MIT
Files
1 file

What it does

This skill teaches an agent to run a repeatable pipeline that turns scattered information, mostly emails such as investor updates, receipts and company metrics, into a clean markdown table. The agent searches your brain first, then email, web and APIs, saves every raw source before extracting fields, removes duplicates, and adds each new row to a tracker page with a link back to its source. Behaviour is set by YAML recipes that define the search queries, classification rules and table format, so the same pipeline can handle different kinds of data.

Great for

  • Founders or operators tracking investor updates, MRR, runway or headcount from email over time
  • People who want a personal expense or subscription ledger built from receipt emails
  • Teams maintaining a source-linked spreadsheet-style tracker inside the GBrain knowledge base

Skip it if

  • One-off questions or quick web lookups, since the seven-phase pipeline is heavy and writes data (mutating: true)
  • Sensitive finances or private email without reviewing what the agent is allowed to read, because it uses an email credential gateway and writes to your brain
  • Financial or legal decisions based on extracted numbers without checking the saved raw sources, since the skill itself warns that LLM-only extraction can be wrong

Try asking

  • “Track investor updates from my inbox this year and build an MRR and runway table with source links”
  • “Extract all receipts from subscription emails into an expense tracker for Q1”
  • “Build a tracker of donations from the last six months and deduplicate repeated entries”
  • “Pull metrics from our portfolio company update emails into a company-updates page”
Step-by-step guide: how to use Data Research PipelineInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    data-research.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip data-research.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip data-research.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Review the saved raw sources and recipe rules before trusting totals, since the skill relies on deterministic regex first and logs LLM fallbacks
  • Start with a built-in recipe such as expense-tracker, then copy and edit it for a custom tracker rather than writing a recipe from scratch
  • Limit the email query window (monthly or quarterly) to keep results manageable and avoid pulling more data than needed

What's inside

  • SKILL.md

Redistributed unmodified from garrytan/gbrain under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.