A standardized communication and verification framework for C-suite AI agent teams to collaborate without loops or chaos.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install c-suite-agent-protocol
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install c-suite-agent-protocol using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Inter-Agent Protocol?
The Inter-Agent Protocol is a technical framework designed for high-level orchestration of C-suite agent teams. It provides a formal syntax for agents representing roles like the CEO, CFO, and CTO to communicate, query each other, and conduct cross-functional analysis. By using this skill within Openclaw Skills, developers can ensure their agentic workflows remain stable, logical, and free from the common pitfalls of multi-agent systems such as infinite loops and circular reasoning.
At its core, the protocol enforces a structured lifecycle for information, moving from raw queries to peer-verified findings and finally to polished, actionable executive summaries. It transforms a collection of isolated models into a cohesive executive board capable of handling strategic business decisions with a high degree of confidence and transparency.
Inter-Agent Protocol Use Cases
- Orchestrating complex cross-functional business analysis between specialized AI agents.
- Running autonomous board meetings where multiple executive roles must reach a consensus.
- Peer-verifying financial projections against operational capacity and market realities.
- Preventing logic loops and depth-related performance degradation in large agent chains.
- Generating standardized, bottom-line-focused reports for human founders and stakeholders.
How Inter-Agent Protocol Works
- An agent triggers a request using the standardized
[INVOKE:role|question]syntax to access domain-specific data from another role. - The protocol automatically tracks the call chain and enforces loop prevention rules, blocking self-invocations or depth exceeding two hops.
- The invoked agent provides a structured response including key findings, supporting data, and a confidence score (high, medium, or low).
- Cross-functional findings undergo a Peer Verification process where relevant departments (e.g., CFO for budget, CTO for feasibility) validate the claims.
- For strategic decisions, an Executive Mentor agent performs a Critic Pre-Screen to identify vulnerabilities or missing perspectives.
- The final output is synthesized into a standardized communication format, prioritizing the bottom line and actionable items for the user.
Inter-Agent Protocol Setup
To implement this protocol within your Openclaw Skills environment, you must configure your agent system prompts to recognize the invocation syntax and lifecycle rules. Reference the following configuration structure:
# 1. Define the invocation and response patterns
# 2. Set loop prevention constraints (MAX_DEPTH=2)
# 3. Load the role definitions for the C-suite suite
# 4. Initialize the peer-verification and critic pre-screen loops
Ensure all agents have access to the company-context.md and decision-log files to maintain consistency across the orchestration layer.
Inter-Agent Protocol Data Schema & Taxonomy
| Component | Description | Syntax/Structure |
|---|---|---|
| Invocation | The standard syntax for inter-agent queries | `[INVOKE:role |
| Call Chain | Metadata tracking the sequence of agents involved | [CHAIN: roleA -> roleB] |
| Response Block | Structured data return for consistent parsing | [RESPONSE:role]...[/RESPONSE] |
| Verification Tag | Indicators for data reliability and source | [VERIFIED] or [ASSUMED] |
| Conflict Flag | Signal for contradictory data between agents | [CONFLICT: agent1 vs agent2] |
| Output Format | The finalized structure for human delivery | Bottom Line / What / Why / How |
Inter-Agent Protocol Advanced Features
- Strict Loop Prevention: Hard rules that block circular calls and depth-heavy chains to preserve context window and prevent reasoning failures.
- Broadcast Pattern: Enables the CEO agent to simultaneously query all roles for rapid impact assessment during crisis management.
- Isolation Enforcement: A dedicated phase in the board meeting protocol that prevents groupthink by forcing agents to form independent views before cross-pollination.
- Internal Quality Loop: A multi-stage verification process including self-audit, peer-review, and critic pre-screening for high-stakes strategic decisions.
- Confidence-Weighted Analysis: Automated resolution of conflicting data points by weighting responses based on verified source material and agent confidence scores.
SKILL.md
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