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Ceo Council

Community
serejaris
ceo-council

Use when needing strategic project analysis from multiple independent expert perspectives. Triggers on business decisions, growth strategy, product direction, competitive analysis, or any situation where diverse C-level opinions reduce blind spots

Overview

Publisherserejaris
Repositorypersonal-corp-os
Skill nameceo-council
Stars
232
Forks
26
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Ceo Council 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.
    https://github.com/serejaris/personal-corp-os/tree/main/skills/ceo-council
  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/serejaris/personal-corp-os.git /tmp/personal-corp-os
mkdir -p .claude/skills
cp -r /tmp/personal-corp-os/skills/ceo-council .claude/skills/ceo-council
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ceo Council 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 Ceo Council 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 Ceo Council 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.

CEO Council — Independent Strategic Analysis

Launch parallel sub-agents as isolated C-level experts. Each analyzes the same project data from their perspective. No coordination between experts — isolation produces genuine diversity of opinion. Then synthesize consensus and disagreements.

Critical: How to Launch Experts

MUST use the Task tool with subagent_type: "general-purpose" and model: "opus".

Task(
  subagent_type: "general-purpose",
  model: "opus",
  prompt: "<expert prompt with data>",
  description: "CFO analysis"
)

DO NOT use bash, shell scripts, or background commands to launch experts. They will fail.

Launch all experts in a single message with multiple Task tool calls for true parallelism.

Step 1: Scan Project Context

Before suggesting experts, understand the project:

  1. Read CLAUDE.md (or README.md if absent)
  2. Scan .claude/rules/ for domain context
  3. Glance at top-level file structure

Based on findings, generate 4-6 expert roles tailored to THIS project. Roles must reflect the project's actual domain, challenges, and stage.

Step 2: Assemble the Council

MANDATORY: Ask the user before proceeding. Do not pick roles yourself.

Use AskUserQuestion with multiSelect: true:

  • Show 4-6 role options with short descriptions of their focus
  • User can always pick "Other" to define custom roles
  • Minimum 2 experts. If user picks 1, suggest adding one more for productive disagreement

Role Examples by Project Type

Don't copy these — generate fresh roles based on actual project context:

Project TypeTypical Roles
SaaSHead of Engineering, Head of Product, Head of Growth, CFO, UX Researcher
Open SourceCommunity Manager, Technical Architect, DevRel, Security Advisor
Content / MediaContent Strategist, Audience Analyst, Monetization Expert, Distribution Expert
EdTechCMO, CFO, CPO, COO, Growth Advisor
E-commerceHead of Supply Chain, Marketing Director, CTO, Customer Experience Lead
Agency / ConsultingSales Director, Delivery Lead, Talent Manager, CFO

Step 3: Gather Current Data

Collect project state to feed all experts. Stay focused on what's relevant:

Read:

  • Key metrics/data files identified during context scan
  • Strategy and planning documents
  • Recent decisions or changes (git log --oneline -10)
  • Previous council analyses (if any)

Skip: GitHub traffic stats, stargazer counts, clone data, contributor lists — these are vanity metrics, not strategic data.

All experts must receive identical data context. Prepare the data block ONCE, then paste it into each expert prompt.

Step 4: Generate Expert Prompts

For each selected expert, create a prompt with the SAME data block:

You are the [ROLE] for [PROJECT NAME]. Analyze the data below from a [DOMAIN] perspective.

Focus on:
- [3-6 specific focus areas relevant to role and project]

Data:
[CURRENT PROJECT DATA — identical for all experts]

[Role-specific instruction: "show the math", "be the contrarian", "prioritize by effort/impact", etc.]

Respond in the same language as the data provided.

Rules:

  • Each expert gets the SAME data block — prepare it once, reuse
  • Focus areas must be specific to the project, not generic
  • Include a personality instruction (contrarian, pragmatic, data-driven)
  • Mention project constraints the expert should know

Step 5: Execute

Launch ALL selected experts in one message using multiple Task tool calls:

# In a single response, call Task for each expert:
Task(subagent_type: "general-purpose", model: "opus", prompt: "<CFO prompt>", description: "CFO analysis")
Task(subagent_type: "general-purpose", model: "opus", prompt: "<CPO prompt>", description: "CPO analysis")
Task(subagent_type: "general-purpose", model: "opus", prompt: "<CTO prompt>", description: "CTO analysis")

Wait for all experts to return results before proceeding to synthesis.

Step 6: Synthesize

Do not skip this step. The synthesis is the entire value of the council.

After all experts report, create a synthesis document:

markdown
# Council Session: [DATE]

## Council Members
[List of selected experts and their focus]

## Context
[Current metrics/state snapshot — brief]

## [Expert 1 Name]
[Key findings and recommendations]

## [Expert 2 Name]
[Key findings and recommendations]

## Consensus (all agree)
1. ...
2. ...

## Disagreements
| Expert | Position | Argument |
|--------|----------|----------|
| ... | ... | ... |

## Decisions
_To be filled after discussion._

Save Results

Save to a logical location:

  • docs/council-[DATE].md — default
  • Or project-specific path if context suggests one

Common Mistakes

MistakeFix
Picking roles without asking userALWAYS use AskUserQuestion first
Using bash to launch expertsONLY use Task tool with subagent_type: "general-purpose"
Giving experts different dataPrepare ONE data block, paste into all prompts
Gathering vanity metricsFocus on project docs, strategy, actual metrics
Too many experts (6+)3-4 is optimal for signal-to-noise
Skipping synthesisThe synthesis IS the value — never skip

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 Ceo Council AI skill do?

Use when needing strategic project analysis from multiple independent expert perspectives. Triggers on business decisions, growth strategy, product direction, competitive analysis, or any situation where diverse C-level opinions reduce blind spots

Why use Ceo Council on TypingMind?

Because you install it once and use it with any model. Ceo Council 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 Ceo Council in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/serejaris/personal-corp-os/tree/main/skills/ceo-council. 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 Ceo Council?

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 Ceo Council?

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

Is the Ceo Council AI skill free?

Yes. It is published on GitHub by serejaris 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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