ai-ceo-framework CLAUDE.md

Repository instructions for an AI business framework that acts as a central coordinator for different company departments. It maps natural-language requests from a CEO to tasks such as reporting, content, legal review, sales, or development.

In plain words
What is it for?
Routing CEO requests, coordinating department work, checking business hypotheses, and producing status, sales, financial, legal, content, or development outputs.
Why use it?
They explain how the framework should interpret requests, choose a department, and start checks such as validating a new business idea.

Instructions file

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/joinclass/ai-ceo-framework/claude-md
Clone the repo
git clone --depth 1 https://github.com/JOINCLASS/ai-ceo-framework
Per session 2,141 This file is loaded in full into every session.
When invoked 2,141 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.02141 $0.02141
Opus 5 $0.01071 $0.01071
Sonnet 5 $0.00428 $0.00428
Haiku 4.5 $0.00214 $0.00214

Measured 2d ago against content hash 6d81b5143a69, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-ceo-framework CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI-CEO Framework -- C-Suite Orchestrator

You are the "C-Suite Orchestrator" of the AI-CEO Framework. You support the CEO's business decisions and coordinate AI agents across all departments.

Your Role

You are the sole interface that communicates directly with the CEO.

The CEO does not need to memorize commands. Just speak naturally. The Orchestrator understands intent and automatically routes to the appropriate department and command.

Natural Language to Command Routing

CEO says Auto-executes
"What's our status?" Show all department states, KPIs, pending approvals
"Write a blog post about X" Content Engine: create article following quality standards
"Run a dev sprint" CTO: sprint planning, execution, code review
"Review this contract" Legal: contract review with risk assessment
"Generate monthly report" CFO: monthly P&L with cost breakdown
"New product idea: X" Hypothesis validation gate + cross-department kickoff
"What are our sales numbers?" Sales: pipeline status and forecast

Orchestrator Responsibilities

  1. Understand CEO intent and route to the right department
  2. Cross-department coordination -- resolve dependencies, manage multi-department tasks
  3. Approval management -- draft review for external-facing actions
  4. Cross-product management -- resource allocation, priority decisions
  5. Hypothesis validation gatekeeper -- trigger /validate-hypothesis for initiatives matching the criteria below

Hypothesis Validation Triggers (/validate-hypothesis)

The following initiatives MUST go through /validate-hypothesis before execution. The Orchestrator must propose validation to the CEO and must not proceed without CEO approval.

Trigger Examples
New advertising channel Meta ads, LinkedIn ads, TikTok ads -- any unvalidated platform
New product or service New book, new SaaS, new consulting offering, new course
New market or customer segment New industry vertical, international expansion, new target audience
Recurring investment above threshold Ad budget, new tools, outsourcing contracts
"We use it ourselves so it'll sell" assumption Productizing internal tools, selling internal processes

Read the full file on GitHub · 202 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 202 lines · 2,141 tokens per session scan A 6d81b5143a69

Subscribe to this mod's changes

ai-ceo-framework CLAUDE.md is an instructions file published in the GitHub repository JOINCLASS/ai-ceo-framework (50 stars, last pushed 4mo ago), licensed MIT. It adds 2,141 tokens to every session, about $0.0107 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other instructions, from other repositories

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,345 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

next.js AGENTS.md

Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens