Third Brain V6 Skills
Production-ready Agent Skills for Claude Code, Codex, Gemini, Cursor, and Windsurf. Build a persistent knowledge operating system with verification-first workflows, Obsidian provenance, scheduled loops, context management, and multi-agent orchestration.
Install 19 reusable agent skills for ingesting sources, compiling interlinked wikis, running daily knowledge loops, verifying claims before shipping, managing token costs, engineering bounded agent loops, and orchestrating multi-agent teams.
Use this if:
- Your AI agent keeps forgetting context between sessions
- You want to enforce verification gates before "done" claims
- You need to structure knowledge as linked pages (like Obsidian) instead of scattered chat history
- You're building agent workflows that should learn and compound over time
- You want Obsidian wiki knowledge to update skills, SOPs, schemas, and automation through supervised promotion gates
Quick Start
1. Clone & Install
git clone https://github.com/Mark393295827/third-brain-v5-skills.git
cd third-brain-v5-skills
bash install.sh claude # or: codex, gemini, cursor, windsurf, all
2. Try a Skill
Paste this into Claude Code or your agent:
Use wiki-ingest on this source. Create source notes, concept pages, entity pages, navigation updates, and a verification summary.
Then paste a URL, article, PDF text, or any source you want to capture.
3. Next Steps
See the 3-Minute Quickstart for a complete walkthrough.
Full guide: GUIDE.md
The Problem
| Scenario | Before | After |
|---|---|---|
| Research PDF | Summarized once, then forgotten | wiki-ingest: source notes, concept pages, linked wiki |
| Coding session | Agent: "I fixed it" (no proof) | verify-before-claim: requires test output + exit code before any claim |
| Daily work | Tasks and ideas scatter across chat | daily-okr: one insight, one wiki update, one action, one output, daily score |
V6 Operating Model
V6 treats the wiki as the agent's durable disk and governance layer:
Input -> Source -> Wiki compile -> Daily loop -> Agent/Wiki flywheel -> Skill/SOP upgrade -> Verification
The upgrade adds six hard defaults:
- Source provenance stays immutable: raw source notes and block refs remain the audit layer.
- Loops have contracts: Trigger -> Execute -> Verify -> State, with budgets and recovery.
- Context is zero-overhead by default: hot paths load only what the task needs.
- Automation is bounded: scans and queues can run unattended; semantic writes stay supervised.
- Teams need ownership: multi-agent work requires write scopes, IPC, join gates, cleanup, and evidence.
- Rules promote through evidence: wiki insights become schema or skill rules only after repeated support and a cheap check.
See V6 release notes.
Core Skills (Start Here)
🧠 Knowledge & Verification
| Skill | What it does |
|---|---|
| wiki-ingest | Capture sources (articles, PDFs, transcripts) into an interlinked wiki with source references, concept pages, and entity pages. Enforces the V6 source-to-skill promotion gate so pages explain why something matters and when it can change future agent behavior. |
| verify-before-claim | Iron rule: No completion claims without fresh verification evidence. Run the proof command, show the output, then claim. Prevents "should work" hallucinations. Uses poker psychology (expected value thinking) to distinguish process from outcomes. |
📅 Daily Loop
| Skill | What it does |
|---|---|
| daily-okr | Execute a 7-KR cycle: Input → Cognition → Wiki → Behavior → Creativity → Output → Feedback. Includes Stop Doing List (Buffett/Munger) to identify what NOT to do. Score: 3=starting, 5=minimal loop, 7=quality, 10=flywheel. |
🎯 Behavior & Creativity
| Skill | What it does |
|---|---|
| behavior-design | Turn goals into habit systems. Decompose → minimum habits → triggers → SOPs → review. Includes Human Agency Scale (HAS) from BJ Fogg. |
| creativity-engine | Generate novel ideas via combinatorial creativity. Lego Building Blocks method (Andrew Ng), cross-domain analogies, minimum experiments. |
🔬 Research & Quality
| Skill | What it does |
|---|---|
| deep-research | STOW-compatible research harness with evidence trails, source/claim ledgers, privacy checks, and direct handoff to wiki-ingest. |
| session-learn | Extract knowledge patterns from sessions — concepts, entities, corrections, patterns, ideas, decisions, gaps. Closure protocol ensures learning feeds back into the wiki. |
📊 Context & Engineering
| Skill | What it does |
|---|---|
| context-manager | Manage LLM context window — token budgeting, prompt assembly, truncation strategies using Concrete Ideas framework (Andrew Ng) + Tokenmax techniques. |
| loop-engineering | Turn repeatable tasks into bounded agent loops with a durable contract, independent verifier, hard budgets, explicit stop/recovery rules, and conservative topology selection. |
| agentic-engineering | Design agent workflows as spec-driven macro actions with quality ceilings, verification gates, delegated-action boundaries, and state checkpoints. |
| agent-teams-command | Orchestrate multi-agent fleets — ownership, IPC, async budget envelopes, integration joins, evidence gates. |
Complete Skill List
📥 Ingestion & Knowledge
wiki-ingest— Ingest sources with source-risk taxonomy, Karpathy understanding gate, concept/entity pages, wikilinksknowledge-ops— Multi-layer knowledge management: classify, deduplicate, preserve evidence hierarchy, vector + Markdown retrievalwiki-lint— Health check: P0/P1 graph health, frontmatter, source refs, wikilink density, provenance debt
🔄 Daily Workflow
daily-okr— 7-KR closed loop with Stop Doing List (Buffett/Munger), daily scorecognitive-compile— 8-section framework: Question → Facts → Concepts → Pattern Recognition → Conflict Detection → Hypothesis Generation
🎨 Behavior & Creativity
behavior-design— Goals → habits → triggers → SOPs → review (HAS framework)creativity-engine— Combinatorial creativity: Lego Building Blocks, cross-domain analogies, minimum tests
🔬 Research & Quality
deep-research— STOW-compatible research harness, evidence trails, source/claim ledgersverify-before-claim— Verification gates, poker psychology (expected value), red-flag detection
🔄 Learning & Flow
session-learn— 7 signal types: concepts, entities, corrections, patterns, ideas, decisions, gapsproject-flow-ops— Execution flow: triage, plan, track, review across projects
📊 Context & Cost
context-manager— Token budgeting, prompt assembly, truncation strategiestoken-cost-tracker— Estimate, log, report token usage with built-in Python logger
🏗️ Engineering
loop-engineering— Bounded loop contracts, independent verification, finite budgets, stop/recovery rules, and topology selectionagentic-engineering— Spec-driven macro actions, quality ceilings, verification gates, state checksharness-engineering— Runtime infrastructure: permissions, system-call tools, delegated gates, provenance, observabilityagent-teams-command— Multi-agent orchestration: ownership, IPC, async budgets, evidence gates
💼 Strategy & Operations
startup-evaluation— Startup health: entrepreneurship, VC 5T, PMF, runway, team, unit economicsanthropic-os— Self-evolving work method engine: CASH growth, 70/30 rule, two-week rule, working backwardsai-six-sigma-property-os— AI + Ontology + DMAIC for property work orders, dispatch, quotes, evidence
How These Skills Fit Together
LLM (CPU) + Context (RAM) + Wiki (Disk)
External Sources ──→ wiki-ingest + knowledge-ops ──→ Knowledge Layers
↓
Daily Loop (daily-okr)
/ / \ \ \
Input Cognition Wiki Behavior Creativity
|
Output → Feedback
↓
session-learn (extract patterns)
↓
verify-before-claim (quality gate)
↓
Multi-agent teams (agentic-engineering)
The system is a closed loop: ingest sources → process daily → extract learning → verify claims → promote rules → scale to teams.
Architecture & Design
Third Brain V6 treats agents as LLM OS processes:
- LLM = CPU
- Context = RAM
- Wiki/Obsidian = Disk
- Tools = System calls
- Skills = Executable programs
- Harness = Kernel
- Agent teams = Processes
Design Layers
| Layer | Principle | Skills |
|---|---|---|
| 🧠 Knowledge OS | Capture, structure, lint, and promote knowledge over time | wiki-ingest, knowledge-ops, wiki-lint |
| ⚡ Daily Loop | Close the knowledge-to-action cycle every day | daily-okr, cognitive-compile |
| 🎯 Behavior & Creativity | Turn knowledge into habits and novel ideas | behavior-design, creativity-engine |
| 🔬 Research & Quality | Verify before claiming, research with rigor | deep-research, verify-before-claim |
| 🔄 Continuous Learning | Extract patterns from every session | session-learn, project-flow-ops |
| 📊 Context & Cost | Manage the LLM's scarcest resource | context-manager, token-cost-tracker |
| 🏗️ Engineering | Design bounded loops, harnesses, agent workflows, and multi-agent systems | loop-engineering, agentic-engineering, harness-engineering, agent-teams-command |
| 💼 Strategy & Operations | Evaluate startups, design AI quality systems | startup-evaluation, anthropic-os, ai-six-sigma-property-os |
Skill Adoption Path
Start small. Add skills as you need them.
| Stage | Core Skills | Unlock When |
|---|---|---|
| Week 1 | wiki-ingest + verify-before-claim |
You can ingest 1 source/day + every claim has fresh evidence |
| Weeks 2-4 | + daily-okr + session-learn |
Daily OKR score >70% for a week, learnings feed back to wiki |
| Month 2+ | + cognitive-compile + behavior-design + creativity-engine |
Wiki has 50+ pages or repeated decisions need synthesis |
| Month 3+ | + knowledge-ops + loop-engineering + harness-engineering + agentic-engineering |
Retrieval, looping reliability, permissions, or delegated actions become bottlenecks |
| Multi-agent | + agent-teams-command + project-flow-ops |
Work splits into separate owners with clear integration gates |
| Strategy | + startup-evaluation + anthropic-os + deep-research |
Need startup health, market, operating-system decisions |
| Operations | + ai-six-sigma-property-os |
Need measurable service quality, dispatch, evidence loops |
Installation
For Claude Code
# Personal skills (available across all projects)
cp -r skills/* ~/.claude/skills/
# Project skills (shared with team)
cp -r skills/* .claude/skills/
For Cursor
mkdir -p .cursor/rules && cp adapters/cursor/third-brain-skills.mdc .cursor/rules/
For Windsurf
mkdir -p .windsurf/skills .windsurf/rules
cp -r skills/* .windsurf/skills/
cp adapters/windsurf/third-brain-skills.md .windsurf/rules/
For Codex CLI / Gemini CLI
cp -r skills/* ~/.agents/skills/ # Codex
cp -r skills/* ~/.gemini/skills/ # Gemini
Full guide: GUIDE.md
Example Workflows
Each workflow is copyable into your agent. See examples/ for complete, verified examples:
- 3-minute quickstart — Fastest path to useful output
- Research PDF to wiki — Turn a source into linked pages
- Verified code session — Use verification gates before claiming a fix
- Daily knowledge loop — Run a compact daily OKR workflow
- Startup evaluation sprint — Turn an idea into validated assumptions
Wiki Structure
Skills default to STOW paths (configurable via system/config.md):
sources/ ← Immutable source notes (articles, PDFs, transcripts)
wiki/
├── concepts/ ← Ideas, frameworks, methods
├── entities/ ← People, companies, products
├── atomic-notes/ ← Single-fact notes
├── outputs/ ← Reusable reports, analyses
├── decisions/ ← Architecture decisions
└── sops/ ← Standard operating procedures
system/ ← Config, log, schema, templates
08_behaviors/ ← Behavior system (goals, habits, reviews)
09_creativity/ ← Creativity system (ideas, experiments)
Tools & References
| Resource | Purpose |
|---|---|
| tools/index.html | Visual skill navigator and dashboard |
| tools/token-calculator.html | Token cost calculator |
| GUIDE.md | Full installation & troubleshooting |
| CLAUDE.md | Claude Code setup |
| CONTRIBUTING.md | How to contribute skills |
What This Is NOT
- Not a chat wrapper. Skills are executable prompts that agents follow; they're not productivity theater.
- Not a productivity tool with 100 metrics. Daily OKR has 7 KRs; that's it. Scoring is 3/5/7/10, not a complex formula.
- Not an all-in-one framework. Pick skills incrementally. You don't need all 18 to start.
- Not prescriptive. Adapt paths, frontmatter, and skill triggers to your workflow.
Philosophy
Three core principles:
- Verification first: No "done" without proof. No claims without evidence. Expected value over confidence.
- Knowledge compounds: Every session should improve the wiki, not scatter across chat history.
- Closed loops: Ingest → Process → Learn → Scale → Verify. No loose ends.
Related Work
- Agent Skills Format — Open specification for agent skills
- llm-wiki-agent — Original STOW pattern implementation by SamurAIGPT
- Karpathy LLM OS — Conceptual framework
Contributing
Bug reports, skill improvements, and PRs are welcome. See CONTRIBUTING.md and CHANGELOG.md.
License
MIT — see LICENSE.
Transparency Note
This project includes growth and outreach tools (in tools/ and outreach/) designed to help the repository reach users via GitHub search and Awesome lists. These tools are optional, dry-run-by-default, and separate from the core skills. If you're installing skills for your own workflow, you don't need them.
The skill frameworks and philosophy are genuine. Use what works for you; ignore what doesn't.
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