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Article Enrichment

CommunityPopular
garrytan
article-enrichment

Transform raw article text dumps in the brain into structured pages with executive summary, verbatim quotes, key insights, why-it-matters, and cross-references. Replaces walls-of-text with quotable, actionable brain pages.

Overview

Publishergarrytan
Repositorygbrain
Skill namearticle-enrichment
Stars
30.1K
Forks
4.5K
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by garrytan on GitHub. Read the source before you install it.

Installation

Install the Article Enrichment AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/garrytan/gbrain.git /tmp/gbrain
mkdir -p .claude/skills
cp -r /tmp/gbrain/plugin/skills/article-enrichment .claude/skills/article-enrichment
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Article Enrichment in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Article Enrichment on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Article Enrichment is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

article-enrichment — From Raw Dumps to Useful Brain Pages

Convention: see conventions/quality.md for citation rules, verbatim-quote requirements, and back-link enforcement.

Convention: see _brain-filing-rules.md for filing rules. Article pages live under media/articles/ for raw ingest; personalized one-of-one synthesis output uses the sanctioned media/articles/<slug>-personalized.md exception.

What this does

Takes an article brain page that's a wall of raw extracted text and rewrites it as a structured page with:

  • Executive Summary — 2-3 sentences, the ONE thing worth remembering
  • Why It Matters — connects to the user's specific projects + interests (read from brain context, not assumed)
  • Quotable Lines — 3-5 VERBATIM quotes worth referencing in essays
  • Key Insights — actual insights, not topic labels
  • Surprising or Counterintuitive — what makes this content unique
  • See Also — standard markdown links to related brain pages

Raw source content is preserved in a collapsed <details> section so the original is never lost.

When to invoke

  • New article page lands in the brain via media-ingest with needs_enrichment: true
  • Existing article page is a wall of text under a ## Content header with no synthesis
  • User says a brain page is useless, boring, or a dump
  • An LLM-judge brain-quality eval fails on quotability or actionability for an article page

The pipeline

1. READ      → Open the article brain page; parse frontmatter + body.
2. SCAN      → Look for ## Content (raw dump) and absence of ## Executive Summary.
3. CONTEXT   → gbrain query the article's key entities to ground "Why It Matters".
4. ENRICH    → Sonnet (default) or Opus (for high-value content) restructures.
5. WRITE     → Replace ## Content with the structured sections; preserve raw
               source in <details>; clear needs_enrichment in frontmatter.
6. CROSS-LINK→ Add back-links from referenced people/companies pages
               (Iron Law per conventions/quality.md).

Invocation

The skill itself is markdown instructions to the agent. It does NOT ship a deterministic CLI command in v0.25.1. The agent uses gbrain's existing operations:

bash
# 1. Find candidate pages
gbrain query "needs_enrichment: true type:article" --limit 50

# 2. For each candidate, read the page
gbrain get media/articles/<slug>

# 3. Enrich via the agent's LLM (Sonnet by default; Opus for high-value)
#    The agent reads the raw content + brain context + writes the structured page.

# 4. Write the enriched page
#    Use the put_page operation with the new structured markdown body.

# 5. Cross-link entities
#    For every person/company mentioned, add a timeline back-link.

Quality bar

An enriched page passes if it has:

  • ## Executive Summary (2-3 sentences)
  • ## Quotable Lines with ≥3 verbatim quotes (literal quotes, not paraphrase)
  • ## Key Insights with ≥3 bullets (insights, not topic labels)
  • ## Why It Matters connecting to specific brain context (not generic)
  • ## See Also with standard markdown links (NOT [[wiki-links]])
  • <details> block preserving the raw source content

Model selection

ModelUse whenQuote accuracy
Sonnet (default)Bulk enrichment, most articlesGood — occasionally paraphrases
OpusHigh-value content, original-thinking pieces, longreadsExcellent — respects "verbatim" instruction

Rule: for bulk enrichment, do a Sonnet draft pass and spot-check 5 with the LLM-judge brain-quality eval. If quotes are paraphrased, switch to Opus for that batch.

Link convention

All cross-references use standard markdown links: [Title](relative/path.md). NEVER use [[wiki-links]] — they don't render on GitHub.

Anti-Patterns

  • ❌ Paraphrasing quotes ("the author argues that…"). Quotes are verbatim or they're not quotes.
  • ❌ Generic "Why It Matters" ("this is important because innovation"). Tie to specific brain context or remove the section.
  • ❌ Inventing topic labels and calling them insights. An insight is a thing the article says that you didn't already know.
  • ❌ Discarding the raw source. Always wrap it in <details>.
  • ❌ Re-enriching non-idempotently — check the needs_enrichment flag in frontmatter; skip if already false.

Related skills

  • skills/media-ingest/SKILL.md — creates the raw article pages this skill enriches
  • skills/idea-ingest/SKILL.md — link/article ingestion with author people-page enforcement
  • skills/conventions/quality.md — citation + back-link rules

Contract

This skill guarantees:

  • Routing matches the canonical triggers in the frontmatter.
  • Output written under the directories listed in writes_to: (when applicable).
  • Conventions referenced (quality.md, brain-first.md, _brain-filing-rules.md) are followed.
  • Privacy contract preserved: no real names, no fork-specific filesystem path literals, no upstream-fork references.

The full behavior contract is documented in the body sections above; this section exists for the conformance test.

Output Format

The skill's output shape is documented inline in the body sections above (see "Output", "Brain page format", or equivalent). The literal section header here exists for the conformance test (test/skills-conformance.test.ts).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Article Enrichment AI skill do?

Transform raw article text dumps in the brain into structured pages with executive summary, verbatim quotes, key insights, why-it-matters, and cross-references. Replaces walls-of-text with quotable, actionable brain pages.

Why use Article Enrichment on TypingMind?

Because you install it once and use it with any model. Article Enrichment is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Article Enrichment in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/garrytan/gbrain/tree/master/plugin/skills/article-enrichment. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Article Enrichment?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Article Enrichment?

As many as you like. As long as a model supports skills, you can use Article Enrichment with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Article Enrichment AI skill free?

Yes. It is published on GitHub by garrytan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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