Third Brain V8.1 Skills: LLM wiki kit by Markk-gao

What it is

agent wiki +engineering skills

— the description by Mark393295827

AutoGineer overview, from the brain’s own files

Third Brain V8.1 provides a structured, verification-first operating model for AI agents, treating the LLM as a CPU, context as RAM, and an Obsidian vault as a durable disk. It offers 21 reusable agent skills designed to manage knowledge ingestion, daily loops, research, and multi-agent orchestration. The system enforces strict provenance, governance, and quality gates, ensuring that agent actions are backed by evidence and that knowledge compounds over time through a structured taxonomy.

How it works

Memory model: LLM wiki

AutoGineer overview, from the brain’s own files

The system organizes information into a structured folder hierarchy including sources, concepts, entities, and maps. It uses a 5-stage worker assembly pipeline (Ingest, Cognitive, GraphWeaver, Governance, Deliverable) to process information. Skills are executed as programs within a harness that provides scheduling, permissions, and observability. It relies on a transactional runtime to manage state and ensure that all knowledge updates are verified and linked within the Obsidian vault.

Folders
Folder	Role	Files
.github	agent-config	5
assets	attachments	5
commands	agent-instructions	4
docs	docs	21
examples	examples	10
hooks	hooks	1
skills	agent-instructions	40
sources	raw-sources	13
tests	tests	8
tools	scripts	51
adapters	folder	2
artifacts	folder	28
contracts	folder	18
core	folder	6
experiments	folder	7
maps	folder	1
outreach	folder	46
system	folder	33
workflows	folder	1

Requirements

Works with: Claude Code, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Amp, Cline, JetBrains Junie, Devin (ex-Windsurf)

Set it up

This brain runs code automatically: 2 scripts. Review install.ps1, install.sh before opening the folder in Claude Code. No step below turns a hook on for you.
- install.ps1: pwsh install.ps1
- install.sh: sh install.sh

Clone the repository at the commit AutoGineer scanned:

git clone https://github.com/Mark393295827/third-brain-v7-skills.git && cd third-brain-v7-skills && git checkout 5a645148a108d71c76521715117b737ae60b1423

Claude Code reads CLAUDE.md from this folder automatically.
cd third-brain-v7-skills && claude
AutoGineer scanned these files at commit 5a64514.
First committed by Mark393295827. Published in Mark393295827/third-brain-v7-skills. Licence: MIT License.

Usage

AutoGineer overview, from the brain’s own files

Ingesting research papers or articles into a linked wiki
Running daily knowledge loops to compound insights
Enforcing verification gates before claiming task completion
Orchestrating multi-agent teams with isolated write scopes
Managing context budgets and state checkpoints for long-running tasks

“Use wiki-ingest on this source. Stage an immutable source, author a governed concept candidate, plan navigation updates, and return a verification summary.”: The agent creates an immutable note in the sources folder, updates the relevant concept pages in the wiki, and provides a summary of the verification steps taken.
“Run the daily-okr skill for today.”: The agent executes the 7-KR cycle, generating a daily insight, updating the wiki, and producing a receipt for the completed work.

Documentation by Mark393295827

Third Brain V8.1 Skills

Verification-first Agent Skills for Codex OS, with optional compatibility adapters for Claude Code, Gemini, Cursor, and Windsurf. Build a persistent knowledge operating system with Obsidian provenance, scheduled loops, bounded static dependency graphs, context management, and multi-agent orchestration.

Install 21 reusable agent skills for ingesting sources, auditing workflows, compiling interlinked wikis, running daily knowledge loops, verifying claims before shipping, managing token costs, engineering bounded loops and static dependency graphs, 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

Image: GitHub stars Image: License: MIT Image: Codex OS Image: Claude Code Image: Cursor Image: PRs Welcome

Quick Start

1. Clone & Install

git clone https://github.com/Mark393295827/third-brain-v5-skills.git
cd third-brain-v5-skills
bash install.sh codex  # Codex is the primary host/kernel

Windows PowerShell uses .\install.ps1 codex. Compatibility adapters require an explicit non-Codex target.

2. Try a Skill

Paste this into Codex:

Use wiki-ingest on this source. Stage an immutable source, author a governed concept candidate, plan navigation updates, and return a verification summary. Treat entity authoring as a separate reviewed capability.

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

Command centre and distribution: V8.1 Codex Agentic OS command centre. Start it with python tools/agentic_os_server.py --state-root .agentic-os-state; the host is localhost-only by default and requires T02 runtime receipts. Claude/Gemini/Cursor/Windsurf remain compatibility adapters, not the primary runtime.

中文历史进阶手册：V7 最大潜力使用手册（参考）

🔥 V8.1 多智能体 Worker 流水线手册 & Worker Flows 规范：事务式流水线（Stage → Author → Graph Plan → Govern → Commit/Postcheck → optional Deliverable），归档只发生在验证提交之后。

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

V8.1 Operating Model

V8.1 keeps the wiki as durable disk and governance, gives every skill a profile-aware execution contract, and makes python -m tools.worker_flow.cli the only canonical transactional runtime:

Input -> Source -> Wiki compile -> Daily loop -> Agent/Wiki flywheel -> Skill/SOP upgrade -> Verification

The upgrade adds seven hard defaults:

Profiles match risk: one-shot, stateful, loop, and high-risk work load only the controls they need.
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 the V8.1 Worker Flow, the Agent Skills standard, and the historical V7 release notes.

V8.1 keeps graph-engineering bounded to static DAGs; dynamic expansion and cyclic graphs remain out of scope.

Core Skills (Start Here)

🧠 Knowledge & Verification

Skill	What it does
wiki-ingest	Preserve an immutable source, compile linked understanding, enforce promotion boundaries, and verify every touched file.
verify-before-claim	Iron rule: no completion claim without fresh, scope-matched evidence; consequential actions also require independent verification, approval, and rollback.

📅 Daily Loop

Skill	What it does
daily-okr	Execute a 7-KR cycle: Input → Cognition → Wiki → Behavior → Creativity → Output → Feedback, with an artifact or receipt for every completed KR.

🎯 Behavior & Creativity

Skill	What it does
behavior-design	Turn outcomes into observable minimum behavior, cues, SOPs, recovery, evidence, and review.
creativity-engine	Generate mechanism-diverse options, rank evidence gaps, and define three bounded 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	Derive budgets at runtime, checkpoint state, compact with KEEP/SUMMARIZE/DROP/RETRIEVE, and route by capability.
loop-engineering	Control temporal depth: turn repeatable work into a bounded Trigger -> Execute -> Verify -> State loop with durable state, finite budgets, and explicit stop/recovery rules.
graph-engineering	Control dependency width: validate bounded static DAGs with explicit dependencies, independent branches, typed joins, and node-local recovery.
agentic-engineering	Design agent workflows as spec-driven macro actions with quality ceilings, verification gates, delegated-action boundaries, and state checkpoints.
harness-engineering	Provide the runtime scheduler, permissions, leases, tools, provenance, and observability needed to execute agent workflows safely.
agent-teams-command	Admit and command multi-agent processes with exclusive ownership, typed IPC, isolated writes, serial integration, evidence, and cleanup.

Complete Skill List

📥 Ingestion & Knowledge

wiki-ingest — Stage immutable sources, author governed concept candidates, plan graph updates, and hand off optional entity authoring for separate review
knowledge-ops — Multi-layer knowledge management: classify, deduplicate, preserve evidence hierarchy, vector + Markdown retrieval
wiki-lint — Health check: P0/P1 graph health, frontmatter, source refs, wikilink density, provenance debt

🔄 Daily Workflow

daily-okr — 7-KR evidence cycle with minimum-day degradation and durable closeout
cognitive-compile — 8-section framework: Question → Facts → Concepts → Pattern Recognition → Conflict Detection → Hypothesis Generation

🎨 Behavior & Creativity

behavior-design — Outcome → minimum behavior → cue → SOP → evidence → review
creativity-engine — Mechanism-diverse combinations, scoring, and falsifiable minimum tests

🔬 Research & Quality

deep-research — STOW-compatible research harness, evidence trails, source/claim ledgers
verify-before-claim — Fresh scope-matched evidence, independent checks, approval, rollback

🔄 Learning & Flow

session-learn — 7 signal types: concepts, entities, corrections, patterns, ideas, decisions, gaps
project-flow-ops — Execution flow: triage, plan, track, review across projects

📊 Context

context-manager — Runtime budgets, checkpoint replay, compaction, retrieval, capability routing

Utility command: commands/token-cost-tracker.md estimates, logs, and reports token usage; it is not one of the 21 Agent Skills.

🏗️ Engineering

loop-engineering — Temporal depth through bounded loop contracts, independent verification, finite budgets, and stop/recovery rules
graph-engineering — Dependency width through bounded static DAGs, explicit branches, typed joins, and node-local recovery
agentic-engineering — Spec-driven macro actions, quality ceilings, verification gates, state checks
harness-engineering — Runtime scheduler, permissions, system-call tools, delegated gates, provenance, observability
agent-teams-command — Multi-agent process ownership, IPC, integration, async budgets, and evidence gates

💼 Strategy & Operations

startup-evaluation — Startup health: entrepreneurship, VC 5T, PMF, runway, team, unit economics
anthropic-os — Governed operating-system experiments: Four-C, 3B, prediction errors, permission ladder
ai-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)
                             ↓
             Loop depth / Graph dependency width
                             ↓
                Multi-agent teams (agent-teams-command)

The system is a closed loop: ingest sources → process daily → extract learning → verify claims → promote rules → scale to teams.

Architecture & Design

Third Brain V8.1 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	Manage hot context, durable checkpoints, and runtime budgets	context-manager
🏗️ Engineering	Design bounded loops, static dependency graphs, harnesses, agent workflows, and multi-agent systems	loop-engineering, graph-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

Engineering boundaries are deliberate: Loop Engineering controls temporal depth; Graph Engineering controls dependency width; Agent Teams Command controls process ownership, IPC, and integration; Harness Engineering supplies the runtime scheduler, permissions, and observability. A graph node may contain a Loop or Agent Team, but V8.1 does not support dynamic or cyclic graphs.

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 artifacts and verified learnings feed back to the 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
Dependency graph	+ `graph-engineering` after `loop-engineering`	Explicit dependencies, independent branches, typed joins, or node-local recovery create more value than orchestration and review cost
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 Codex CLI (Primary host/kernel)

# Personal skills (available across all projects)
bash install.sh codex

For Cursor

bash install.sh cursor

For Windsurf

bash install.sh windsurf

Compatibility adapters: Claude Code / Gemini CLI

bash install.sh claude
bash install.sh 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/     ← 13 contracted domains
├── entities/     ← people, companies, funds-investors, products, orgs
└── outputs/      ← gmail-digests, evaluations, compilations
maps/
├── domain-mocs/
├── system-indexes/
├── project-maps/
└── canvases/
system/           ← Deployed contracts, config, schema, templates, runs

Tools & References

Resource	Purpose
tools/index.html	V8.1 visual skill navigator
tools/token-calculator.html	Historical V5 cost-model calculator; not a runtime authority
GUIDE.md	Full installation & troubleshooting
V7 最大潜力使用手册（历史参考）	Earlier profile、知识飞轮、Agent 工程、治理和 30 天采用路径
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 seven causally linked KRs with evidence.
Not an all-in-one framework. Pick skills incrementally. You don't need all 20 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.

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.

CHANGELOG.md

Changelog

All notable changes to Third Brain V8.1 Skills are documented here.

Current V8.1 baseline: 21 Agent Skills.

This project follows a small-release rhythm: ship one focused release every 1-2 weeks when there are meaningful fixes, docs improvements, or skill updates.

[8.1.0] - 2026-08-18

Added & Standardized

V8.1.0 Gold-Standard Concept Specification (concept-gold-standard):
- Full schema alignment across system/templates/template-concept-gold-standard.md and template-concept-gold-standard-v8.1.md in both skills repo and Obsidian Vault.
- Complete 10-section contract structure: Frontmatter (contract_version: "8.1.0", knowledge_stage, evidence_level, freshness_tier, source_ids, run_id), Core Thesis callout (> [!NOTE]) with block anchor ^{{concept_slug}}-core-thesis, Temporal Scope (> [!INFO]), Evidence Scope (Direct Evidence, Interpretation, Evidence Boundary, Falsifiers), Core Mechanisms with 3-stage colored Mermaid TD flowchart (#f0f5ff, #f6ffed, #fffbe6), Multi-dimensional Paradigm Matrix, Key Data with source citations, Actionable SOP, 5-category Graph Connections (Domain MOC, People, Companies, Concepts, Immutable Sources), and Evolution Timeline.
System-Wide Schema & Governance Upgrade:
- Upgraded system/schema.md in Obsidian Vault and skills repo to V8.1.0 contract specifications.
- Ensured source cards follow immutable provenance, block-anchored key claims, evidence boundary, and key insights structure.
- Synchronized all template contracts across primary C: Desktop and D: relocated drive repositories.

[7.2.0] - 2026-07-31

Added

Obsidian Vault Multi-Domain Taxonomy Specification (V5.0 / V7.2):
- 13 Concept Domains (ai-engineering, ai-economics, ai-science, behavioral-econ, business-strategy, entrepreneurship, general-concepts, geopolitics-energy, identity-culture, investing-macro, investing-quant, investing-vc, knowledge-systems).
- 5 Entity Categories (people, companies, funds-investors, products, orgs).
- 6 Source Pools (YYYY-MM/ chronological pools, pre-2026/, books/ >100KB).
- 3 Output Categories (gmail-digests/, evaluations/, compilations/).
- 4 Map Tiers (domain-mocs/, system-indexes/, project-maps/, canvases/).
- Active/Historical Log Rotation protocol (system/log.md <100KB, system/logs/log-archive-historical.md).
Integrated updated path contracts across system/config.md, AGENTS.md, GEMINI.md, CLAUDE.md, README.md, and core skills.

Added

graph-engineering for bounded static DAG admission, typed node/edge contracts, explicit joins, single-writer ownership, node-local recovery, and strict validation. It complements rather than replaces loop-engineering.
A reproducible Loop-vs-Graph experiment with positive and negative admission fixtures, provenance hashes, independent review, and explicit claim limits.
Non-empty input, output, done, and non_goals contracts across all skills, enforced by the repository linter.

Fixed

Installer copies now exclude __pycache__, .pyc, and .pyo artifacts across every skill target.
Windows now has a native install.ps1 path with the same targets and cache filtering as install.sh.
Governance and release documentation now use the same lint, test, diff, and strict Loop validation gates as CI.
Hook documentation now distinguishes non-shipped design examples from executable integrations.
Graph strict validation now includes failure routes in DAG checks and binds external effects to exact approval scopes, direct human-gate receipts, allowed write targets, and compensation.
Loop cap validation now rejects unbounded fallback language and parses compound budgets by their relevant units.

Added

ai-six-sigma-property-os skill for designing an AI + Ontology + DMAIC Black Belt operating model for property work orders, dispatch, quotes, evidence, CTQ dashboards, root-cause loops, and MVP quality control.
ChatGPT Deep Research STOW comparison report and official-docs digest for testing deep-research against plan review, source control, activity trace, and safety behavior.
GitHub deep-research top-5 digest translating high-star repository patterns into deep-research skill upgrades.
AI workflow skill-iteration digest translating recent Obsidian AIOS, dynamic workflow, managed-agent, and self-compaction notes into repo skill updates.
Karpathy wiki skill-audit digest translating LLM Wiki, macro actions, AutoResearch boundaries, and agentic education into concrete wiki skill rules.
Wiki ingest governance digest translating recent Obsidian ingest logs, lint report, governance dashboard, and clipping queue rules into skill updates.
Startup health framework digest translating Obsidian startup, VC, efficiency, and primary-investor maps into skill rules.
Google I/O '26 agentic stack digest translating the latest Obsidian wiki ingest into full-stack agent design rules.
Agent understanding framework wiki concept mapping Karpathy LLM OS ideas to Third Brain agent workflow, harness, and team design.
Agent Skills open-format standard document and linter for validating skill folder shape, metadata, trigger descriptions, and quality gate sections.
Agentic Engineering principles document translating spec-driven development, macro actions, security-aware integration, and AutoResearch boundaries into repo standards.
Skill-level assumes, conflicts_with, and ## Success Metrics contracts across all 19 skills.
system/config.md as the default configurable vault path contract for wiki-writing skills.
README skill adoption ladder that makes wiki-ingest + verify-before-claim the recommended first stage.

Changed

Entry docs, adapters, examples, dashboards, and token-cost benchmarks now describe the upgraded deep-research STOW handoff workflow consistently.
deep-research now includes ChatGPT-style preflight, source-access boundaries, activity traces, STOW mapping, private-data safety checks, and wiki-ingest handoff packets.
deep-research now supports research modes, source ledgers, claim ledgers, outline-first synthesis, recency/social signal handling, and Heavy mode gap-fill/adversarial loops.
agentic-engineering, harness-engineering, agent-teams-command, anthropic-os, and context-manager now include workflow complexity gates, dynamic-workflow governance, AIOS 4C/Bike Method audits, managed-agent runtime separation, and long-horizon compaction contracts.
wiki-ingest, wiki-lint, and knowledge-ops now apply a Karpathy-style understanding gate, Markdown-first retrieval default, macro-action scope contract, reusable workflow extraction, and objective-metric boundary for autonomous loops.
wiki-ingest, wiki-lint, and knowledge-ops now include source-risk taxonomy, clipping lifecycle, targeted post-ingest lint, P0/P1 graph health gates, duplicate-source handling, provenance debt, and weak-link review queues.
startup-evaluation now evaluates startup health with stage, evidence ladder, PMF/traction, unit economics, team/governance, runway, VC 5T, AI/hard-tech addendum, top-constraint diagnosis, and next-cheapest-test design.
agentic-engineering, harness-engineering, agent-teams-command, and verify-before-claim now include full-stack agent surfaces: delegated actions, commerce mandates, generated-media provenance, ambient-device privacy, and single-source product claim rules.
agentic-engineering, harness-engineering, and agent-teams-command now share a process/kernel/system-call mental model with explicit write-back and cleanup rules.
README, GUIDE, and CLI entry docs now link or describe the expanded LLM OS architecture mapping.
README and community discovery docs now include stronger launch/discovery paths for GitHub star conversion.
Skill descriptions now use explicit Use when trigger language for better discovery under progressive disclosure.
Core engineering skills now emphasize quality ceilings, macro action specs, adversarial review, and objective evaluation boundaries.
Cursor, Windsurf, Codex, Claude, and Gemini routing docs now enforce assumptions, conflicts, success metrics, and path config before completion claims.
Wiki examples and commands now refer to configurable path variables instead of hard-coded vault directories.
The skill linter now requires assumes, conflicts_with, and ## Success Metrics.

v6.0 - 2026-06-27

Added

V6 knowledge operating system release notes translating Obsidian Agent/Wiki flywheel evidence into skill, SOP, schema, and automation promotion gates.
Daily-loop aware operating model: input -> source -> wiki compile -> daily loop -> Agent/Wiki flywheel -> skill/SOP upgrade -> verification.
V6 promotion gate for wiki insights: repeated durable support, bounded macro action, no provenance relaxation, and cheap objective check before rule promotion.

Changed

Core wiki skills now treat input-skills-obsidian as the front door of the V6 knowledge OS rather than a one-off importer.
Core engineering skills now standardize Trigger -> Execute -> Verify -> State loops with hard budgets, recovery paths, independent evidence, and durable write-back.
Harness and team skills now use zero-overhead context, MCP/Skills/Hooks selection, ownership, IPC, join gates, cleanup, and attention-budget controls as default constraints.

Notes

V6 does not rewrite historical V5 vault pages. Existing source notes remain immutable; historical structure debt stays in lint reports or review queues.

v5.1 - 2026-05-14

Added

README-top system architecture infographic for the LLM + Skills + Obsidian integration.
agentic-engineering skill for model-native workflow refactoring, autonomy defaults, state checkpoints, and verification gates.
GitHub issue templates for bugs and skill requests.
Pull request template with verification and changelog prompts.
Release playbook for feedback triage and small-version cadence.
Simplified README hero diagram.
3-minute quickstart prompt for wiki-ingest.
Before/after usage cases in README.
examples/ workflows for ingest, verification, daily review, and Obsidian entry.
Standard skill template reference.
Cursor and Windsurf compatibility documentation and adapter templates.
Fifth workflow example for startup evaluation.
Animated-style install demo SVG and one-click test prompt.
Community discovery checklist with recommended repository description, topics, and Awesome-list targets.
V5.2 post-ingest closure rules for input taxonomy, behavior conversion, creativity conversion, and governance review.
Architecture walkthrough example for the full LLM + Skills + Obsidian closed loop.

Changed

Public docs now describe the current 17-skill catalog.
Cursor and Windsurf routers now cover knowledge ops, wiki lint, context management, agentic engineering, harness engineering, and Anthropic OS.
Core engineering skills now use a standard ## Quality Gates heading.
README first screen now emphasizes value proposition, quick install, try-it prompts, and local demos.
Each skill now includes a verified-effect statement in its usage template.
Each skill now includes version, update date, and output example metadata.
Dashboard now includes visual navigation shortcuts and skill search.
install.sh now supports explicit codex, claude, gemini, cursor, windsurf, and all targets.
wiki-ingest, cognitive-compile, and creativity-engine now align with the V5 architecture loop from source to behavior, creativity, and governance.

Release Template

Use this shape for each release:

## vX.Y.Z - YYYY-MM-DD

### Fixed
- Short description of the user-visible bug fix.

### Added
- Short description of the new skill, tool, example, or workflow.

### Changed
- Short description of documentation, naming, or behavior changes.

### Notes
- Upgrade or migration notes, if any.

318 files · 7 not served here

Advantages

Enforces verification gates to prevent agents from making unverified claims. evidence: README.md
Provides a durable, structured knowledge base that compounds over time. evidence: README.md
Supports multi-agent orchestration with typed IPC and isolated write scopes. evidence: README.md

Limitations

Does not support dynamic or cyclic graphs; graph-engineering is bounded to static DAGs. evidence: README.md
Requires a specific transactional runtime for full functionality. evidence: AGENTS.md

Security

Risk level: Low risk

This brain runs

Agent instructions that run or fetch something (88)

AGENTS.md: V8.1 defines an explicit **5-Stage Worker Assembly Pipeline** in `workflows/worker-flows.md`, enforced by the canonical transactional runtime `python -m tools.worker_flow.cli`.
AGENTS.md: **loop-engineering** — Temporal-depth control through bounded Trigger → Execute → Verify → State loops, durable contracts, hard budgets, and stop/recovery rules.
AGENTS.md: `## Success Metrics` — minimum observable result for one successful run.
GEMINI.md: V8.1 defines a transactional **5-Stage Worker Assembly Pipeline** (`workflows/worker-flows.md`) enforced by `python -m tools.worker_flow.cli`.
skills/agent-teams-command/SKILL.md: <execute>
skills/agent-teams-command/SKILL.md: Run regression tests.
skills/agent-teams-command/SKILL.md: </execute>
skills/agentic-engineering/SKILL.md: Run the adoption gate: use an agent only when ambiguity/adaptation outweigh orchestration, verification, and maintenance cost.
skills/agentic-engineering/SKILL.md: <execute>
skills/agentic-engineering/SKILL.md: only host code may execute tools or decide continuation.
skills/agentic-engineering/SKILL.md: Run a thin loop: understand -> plan -> smallest change -> targeted test -> inspect diff/state -> broader check.
skills/agentic-engineering/SKILL.md: </execute>
skills/ai-six-sigma-property-os/SKILL.md: bounded agents execute and audit;
skills/ai-six-sigma-property-os/SKILL.md: <execute>
skills/ai-six-sigma-property-os/SKILL.md: </execute>
skills/anthropic-os/SKILL.md: Run Four-C in order: **Context** (truth/history), **Connections** (systems/accounts), **Capabilities** (skills/SOPs/evals), **Cadence** (triggers/reviews).
skills/anthropic-os/SKILL.md: <execute>
skills/anthropic-os/SKILL.md: Run dual prediction when useful: human and agent predict outcome independently;
skills/anthropic-os/SKILL.md: </execute>
skills/behavior-design/SKILL.md: <execute>
skills/behavior-design/SKILL.md: **H3 SOP:** write `trigger -> action -> evidence -> recovery -> stop` so a missed run has a next move.
skills/behavior-design/SKILL.md: </execute>
skills/behavior-design/SKILL.md: run a short observation period before optimizing.
skills/cognitive-compile/SKILL.md: <execute>
skills/cognitive-compile/SKILL.md: </execute>
skills/context-manager/SKILL.md: <execute>
skills/context-manager/SKILL.md: </execute>
skills/creativity-engine/SKILL.md: <execute>
skills/creativity-engine/SKILL.md: </execute>
skills/daily-okr/SKILL.md: Run one daily objective through seven linked Key Results.
skills/daily-okr/SKILL.md: <execute>
skills/daily-okr/SKILL.md: **Behavior:** execute one minimum behavior linked to the objective.
skills/daily-okr/SKILL.md: </execute>
skills/deep-research/SKILL.md: <execute>
skills/deep-research/SKILL.md: Run a broad discovery pass;
skills/deep-research/SKILL.md: Run a gap-fill pass only for decision-critical unknowns.
skills/deep-research/SKILL.md: Run an adversarial pass: strongest counterevidence, alternative mechanism, stale data, selection bias, and missing base rate.
skills/deep-research/SKILL.md: </execute>
skills/graph-engineering/SKILL.md: Run the admission gate before drawing a graph:
skills/graph-engineering/SKILL.md: Probe candidate independence with a small dry run.
skills/graph-engineering/SKILL.md: <execute>
skills/graph-engineering/SKILL.md: Write the JSON contract and run `scripts/validate_graph_contract.py <contract.json> --strict`.
skills/graph-engineering/SKILL.md: node success alone cannot certify graph success.
skills/graph-engineering/SKILL.md: </execute>
skills/graph-engineering/SKILL.md: run only independent ready nodes.
skills/harness-engineering/SKILL.md: Run the trace gate: the harness must be able to show what the agent saw, proposed, called, changed, and verified.
skills/harness-engineering/SKILL.md: <execute>
skills/harness-engineering/SKILL.md: The host decides whether to execute, continue, checkpoint, or escalate;
skills/harness-engineering/SKILL.md: </execute>
skills/harness-engineering/SKILL.md: Verify permissions with actual environment boundaries and run an independent end-to-end trace.
skills/harness-engineering/SKILL.md: A model emits plausible success text with a tool request: validate and execute the tool in host code, then verify its result;
skills/harness-engineering/SKILL.md: A maintenance run finds no eligible change: emit a verified `NO_OP` receipt and zero external outputs rather than creating notification or PR noise.
skills/harness-engineering/SKILL.md: The scheduler ran on time but the state store was stale: block mutation, mark the run failed, and recover from the last verified checkpoint.
skills/harness-engineering/SKILL.md: A Graph worker completes twice after lease expiry: deduplicate by node/run identity and release successors only from one verified transition.
skills/knowledge-ops/SKILL.md: <execute>
skills/knowledge-ops/SKILL.md: **Verify:** read after write, check links/source refs, rerun exact-identity search, and run representative retrieval queries.
skills/knowledge-ops/SKILL.md: Use idempotency keys for machine append operations: derive the key from operation, canonical source identity, target, and run/batch id;
skills/knowledge-ops/SKILL.md: </execute>
skills/knowledge-ops/SKILL.md: make no whole-vault claim.
skills/loop-engineering/SKILL.md: <skill_contract> <input>A repeatable task with inspectable state, finite budgets, permissions, and an independent verifier.</input> <output>A validated Trigger -> Execute -> Verify -> State contract plus resumable run receipts.</output> <done>The declared metric or stop condition is su …[+161 chars]
skills/loop-engineering/SKILL.md: **Goal:** run until a defined end state or cap.
skills/loop-engineering/SKILL.md: <execute>
skills/loop-engineering/SKILL.md: **Act:** execute one bounded action and capture artifact/diff/receipt.
skills/loop-engineering/SKILL.md: </execute>
skills/loop-engineering/SKILL.md: A scheduled job fired but produced no run receipt: status is triggered, not completed;
skills/project-flow-ops/SKILL.md: <execute>
skills/project-flow-ops/SKILL.md: Run the verification named in the definition of done.
skills/project-flow-ops/SKILL.md: </execute>
skills/session-learn/SKILL.md: <execute>
skills/session-learn/SKILL.md: **Pattern** — a reusable Trigger -> Execute -> Verify -> State sequence.
skills/session-learn/SKILL.md: </execute>
skills/startup-evaluation/SKILL.md: <execute>
skills/startup-evaluation/SKILL.md: </execute>
skills/verify-before-claim/SKILL.md: <execute>
skills/verify-before-claim/SKILL.md: Run the selected check after the final material change.
skills/verify-before-claim/SKILL.md: </execute>
skills/wiki-ingest/SKILL.md: record the identity query in the run ledger.
skills/wiki-ingest/SKILL.md: <execute>
skills/wiki-ingest/SKILL.md: Give every machine log entry an idempotency key derived from run/batch, operation, canonical source identity, and target;
skills/wiki-ingest/SKILL.md: **Verify:** run targeted link, source-ref, frontmatter, block-ref, empty-file, navigation, and post-write exact-identity checks over touched files.
skills/wiki-ingest/SKILL.md: </execute>
skills/wiki-lint/SKILL.md: make no content mutation unless separately authorized.
skills/wiki-lint/SKILL.md: <execute>
skills/wiki-lint/SKILL.md: Run twelve checks and preserve file-level evidence:
skills/wiki-lint/SKILL.md: </execute>
skills/wiki-lint/SKILL.md: If repair was authorized, run the relevant check again after each bounded repair.
skills/workflow-audit/SKILL.md: <execute> Extract a bounded list of distinct work candidates.
skills/workflow-audit/SKILL.md: </execute>

Install scripts (2)

install.ps1: pwsh install.ps1
install.sh: sh install.sh

Low risk: scripts-present (install.ps1)
Low risk: scripts-present (install.sh)

Install from source

7 of its files are not served here, so there is no ZIP. Mark393295827/third-brain-v7-skills at 5a64514

What it is

How it works

Requirements

Set it up

Usage

Documentation by Mark393295827

Third Brain V8.1 Skills

Quick Start

1. Clone & Install

2. Try a Skill

3. Next Steps

The Problem

V8.1 Operating Model

Core Skills (Start Here)

🧠 Knowledge & Verification

📅 Daily Loop

🎯 Behavior & Creativity

🔬 Research & Quality

📊 Context & Engineering

Complete Skill List

📥 Ingestion & Knowledge

🔄 Daily Workflow

🎨 Behavior & Creativity

🔬 Research & Quality

🔄 Learning & Flow

📊 Context

🏗️ Engineering

💼 Strategy & Operations

How These Skills Fit Together

Architecture & Design

Design Layers

Skill Adoption Path

Installation

For Codex CLI (Primary host/kernel)

For Cursor

For Windsurf

Compatibility adapters: Claude Code / Gemini CLI

Example Workflows

Wiki Structure

Tools & References

What This Is NOT

Philosophy

Related Work

Contributing

License

Transparency Note

Changelog

[8.1.0] - 2026-08-18

Added & Standardized

[7.2.0] - 2026-07-31

Added

Added

Fixed

Added

Changed

v6.0 - 2026-06-27

Added

Changed

Notes

v5.1 - 2026-05-14

Added

Changed

Release Template

Advantages

Limitations

Security

This brain runs

Attribution and licence

Install from source