Home / garrytan / gbrain · plugin-variants/gbrain-daily/skills/data-research/SKILL.md · GitHub

data-research skillA

data-research is agent-read markdown (skill) from garrytan/gbrain: Structured data research: search sources, extract structured data, archive raw sources, maintain canonical tracker pages, deduplicate. Parameterized via YAML recipes for investor updates, donations, company updates, or any email-to-structured-data pipeline..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# 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
…

Read the whole file at its exact version.

How to install

Latest version
mdr add garrytan/gbrain/data-research@v1.1.0
Exact content
mdr add garrytan/gbrain/data-research@sha256:1dc6161088475e1e

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_ijjhrchmfqansirp.svg)](https://markdownregistry.com/a/art_ijjhrchmfqansirp)

1 badge views in 30 days

Versions

versioncommittedcommitsizeaudit
v1.1.0 latest2026-08-17 489e277 5,169 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (5169 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

garrytan/gbrain · 30,275 stars · license MIT · pushed 2026-09-23 · branch master

API

GET https://markdownregistry.com/api/v1/artifacts/art_ijjhrchmfqansirp
GET https://markdownregistry.com/api/v1/resolve?ref=garrytan/gbrain/data-research
GET https://markdownregistry.com/api/v1/blob/1dc6161088475e1e6d0b0ce7890e4ea1371a321b45adfe877cd312d7ee275e36

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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