Claude Blog Brain logo

Claude Blog Brain

CommunityPopular
AgriciDaniel
claude-blog-brain

Scaffold and operate Claude Blog Brain, a source-cited Obsidian brain for blog content creation, optimization, and management dual-optimized for Google rankings (E-E-A-T, the 2026 core updates) and AI citations (GEO/AEO), spanning writing, rewriting and freshness, SERP-informed briefs and outlines, editorial calendars and strategy, semantic topic clusters, schema and internal linking, multilingual publishing, the FLOW framework, factchecking, personas, distribution, and the blog delivery contract, grounded in the claude-blog skill. Use when the user says "claude-blog-brain", "Claude Blog Brain", "create a blog content creation, optimization, and management dual-optimized for Google rankings (E-E-A-T, the 2026 core updates) and AI citations (GEO/AEO), spanning writing, rewriting and freshness, SERP-informed briefs and outlines, editorial calendars and strategy, semantic topic clusters, schema and internal linking, multilingual publishing, the FLOW framework, factchecking, personas, distribution, and the blog delivery contract, grounded in the claude-blog skill brain", "import sources", "synthesize plan", "render report", or wants a persistent vault-backed operating system for blog content creation, optimization, and management dual-optimized for Google rankings (E-E-A-T, the 2026 core updates) and AI citations (GEO/AEO), spanning writing, rewriting and freshness, SERP-informed briefs and outlines, editorial calendars and strategy, semantic topic clusters, schema and internal linking, multilingual publishing, the FLOW framework, factchecking, personas, distribution, and the blog delivery contract, grounded in the claude-blog skill.

Overview

PublisherAgriciDaniel
Repositoryclaude-blog
Skill nameclaude-blog-brain
Stars
2.2K
Forks
362
Bundled files
479
LicenseCustom
Links
Skill sourceRepositoryHomepage
  • 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.

  • 479 bundled files

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

  • Open source

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

Installation

Install the Claude Blog Brain 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/AgriciDaniel/claude-blog.git /tmp/claude-blog
mkdir -p .claude/skills
cp -r /tmp/claude-blog/brain .claude/skills/claude-blog-brain
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Claude Blog Brain 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 Claude Blog Brain 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 Claude Blog Brain 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.

Claude Blog Brain

Operate the vault first. Read CODEX.md, wiki/hot.md, and wiki/index.md before changing notes.

Commands

bash
/claude-blog-brain new <client-slug> --owner <name>
/claude-blog-brain demo
/claude-blog-brain ingest --vault <path> --file <source>
/claude-blog-brain synthesize --vault <path>
/claude-blog-brain report --vault <path>
/claude-blog-brain visuals --vault <path>
/claude-blog-brain lint --vault <path>
/claude-blog-brain next --vault <path>

Source checkout equivalent:

bash
claude-blog-brain new <client-slug> --owner <name>
claude-blog-brain demo
claude-blog-brain ingest --vault <path> --file <source>
claude-blog-brain synthesize --vault <path>
claude-blog-brain report --vault <path> --html-only

Required Operating Rules

  1. Read <vault>/CODEX.md.
  2. Read <vault>/wiki/hot.md.
  3. Read <vault>/wiki/index.md.
  4. Preserve .raw/ as immutable source material.
  5. Never store credentials in the vault.
  6. Never make domain-specific claims without dated trustworthy sources.
  7. Keep hot, index, overview, and log current.
  8. Record research evidence in references/source-ledger.json.
  9. Record domain adapter completion in references/adapter-manifest.json.

Script Mapping

  • new -> python scripts/scaffold_vault.py
  • demo -> python scripts/build_demo_vault.py
  • ingest -> python scripts/ingest_source.py
  • synthesize -> python scripts/synthesize_brain.py
  • report -> python scripts/render_brain_report.py
  • visuals -> python scripts/generate_vault_visuals.py
  • lint -> python scripts/lint_vault.py
  • next -> python scripts/guide_next_action.py

Quality Gates

  • No ranking or traffic guarantee; content outcomes are probabilistic and never certain
  • No credentials, tokens, API keys, or private client content in repo artifacts
  • No mutation of a CMS, GSC, GA4, or publishing platform; the brain is advisory and read-only
  • No recommendation without a dated source, confidence level, and rollback note
  • No deprecated advice (HowTo schema, retired FAQ rich results, FID) presented as current
  • No fabricated or unsourced statistics and no generic, unsupported, or low-quality generated filler presented as fact

Do not call this brain market-ready unless scripts/audit_brain.py --require market-ready passes. A scaffold is not a finished brain.

Research Refresh

monthly for Google algorithm updates and Search Central policy; before every release for E-E-A-T framing, schema deprecations, and GEO/AEO citation claims; on-changelog for the claude-blog skill

Community

Use public project Discussions for questions and support: https://github.com/AgriciDaniel/claude-blog/discussions. Report reproducible defects through public Issues: https://github.com/AgriciDaniel/claude-blog/issues.

Bundled files

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

and 140 more files.

Frequently asked questions

What does the Claude Blog Brain AI skill do?

Scaffold and operate Claude Blog Brain, a source-cited Obsidian brain for blog content creation, optimization, and management dual-optimized for Google rankings (E-E-A-T, the 2026 core updates) and AI citations (GEO/AEO), spanning writing, rewriting and freshness, SERP-informed briefs and outlines, editorial calendars and strategy, semantic topic clusters, schema and internal linking, multilingual publishing, the FLOW framework, factchecking, personas, distribution, and the blog delivery contract, grounded in the claude-blog skill. Use when the user says "claude-blog-brain", "Claude Blog Br...

Why use Claude Blog Brain on TypingMind?

Because you install it once and use it with any model. Claude Blog Brain 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 Claude Blog Brain in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-blog/tree/main/brain. 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 Claude Blog Brain?

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 Claude Blog Brain?

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

Is the Claude Blog Brain AI skill free?

Yes. It is published on GitHub by AgriciDaniel under the Custom 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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