agent-protocol
by alirezarezvaniagent-protocol is a documentation-based skill for C-suite agent orchestration. It defines invocation syntax, role tokens, response blocks, chain tracking, isolation rules, and loop prevention for auditable multi-agent business workflows.
This skill scores 78/100, which makes it a solid listing candidate for directory users who want structured C-suite multi-agent coordination. It provides enough concrete protocol syntax, role definitions, response conventions, and example chains to help an agent execute with less guesswork than a generic prompt, though adoption is strongest when used with the related advisor skills and the repository could make installation clearer.
- Clear trigger and scope: the description says to use it when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings.
- Operational syntax is concrete, including `[INVOKE:role|question]`, valid role tokens, role-to-advisor mappings, and example invocations.
- The included reference file provides reusable invocation patterns such as a CRO → CFO → CMO revenue planning chain with response formatting and depth-limit guidance.
- Best fit is narrow: it is explicitly designed for C-suite advisor teams, not general multi-agent orchestration.
- No install command or README is present at the skill path, and the protocol appears to assume companion advisor skills for the listed role tokens.
Overview of agent-protocol skill
What agent-protocol is for
The agent-protocol skill defines a lightweight communication protocol for multi-agent executive workflows. It gives C-suite advisor agents a shared syntax for asking each other focused questions, returning structured answers, and preventing uncontrolled recursive calls. Use it when an AI team needs CFO, CTO, CRO, CMO, legal, data, security, or operations perspectives to coordinate without turning into an untraceable chat thread.
Best-fit users and workflows
This agent-protocol skill is best for people building or using agent orchestration around business decisions: board prep, hiring plans, revenue planning, product prioritization, risk review, AI governance, or cross-functional strategy. It is especially useful when one advisor role should own the final synthesis but needs constrained input from other roles. It is less useful for single-agent writing tasks, simple Q&A, or workflows where every role can freely debate without a clear owner.
What makes it different
The practical value is not just the [INVOKE:role|question] tag. The skill also defines valid role tokens, response format expectations, isolation rules, chain notation, and loop-prevention constraints. Those details make agent-to-agent calls auditable: you can see who asked what, which role answered, what confidence level was claimed, and where the chain should stop. For agent-protocol for Agent Orchestration, that structure matters more than a clever prompt because it reduces circular reasoning and runaway delegation.
Adoption considerations
Install this skill if your agent environment can preserve protocol markers such as [INVOKE:cfo|...], [RESPONSE:cfo]...[/RESPONSE], and [CHAIN: cro → cfo → cmo]. The upstream skill is documentation-heavy and has one supporting reference file, references/invocation-patterns.md; there are no scripts or automation hooks. That means it is easy to inspect and adapt, but you must enforce the protocol through your prompts, agent instructions, or orchestration layer.
How to Use agent-protocol skill
agent-protocol install and first files to read
Install from the repository with:
npx skills add alirezarezvani/claude-skills --skill agent-protocol
After installation, read SKILL.md first because it defines the role tokens, invocation syntax, response format, isolation rules, and loop-prevention rules. Then read references/invocation-patterns.md for realistic chains such as revenue planning, board meeting coordination, and cross-functional escalation. The reference file is important because it shows when to invoke another role instead of guessing from the current agent’s perspective.
Inputs the skill needs
Good agent-protocol usage starts with a clear owner, decision, available facts, and allowed roles. A weak prompt says: “Have the C-suite discuss our Q3 plan.” A stronger prompt says: “Act as CRO. Build a Q3 revenue plan. You may invoke CFO for runway constraints and CMO for pipeline assumptions. Stop after two hops. Use the response format and include a final synthesis with open risks.”
That stronger version improves output because it sets the initiating role, business objective, invocation boundaries, and expected synthesis. Without those constraints, agents tend to over-consult, repeat each other, or produce generic executive commentary.
Practical invocation workflow
Use a three-step workflow:
- Assign the lead role. Decide which agent owns the outcome, such as CRO for revenue planning or CTO for engineering feasibility.
- Invoke only for missing expertise. Use
[INVOKE:role|question]when the answer materially depends on another function’s data or judgment. - Synthesize and stop. The lead agent should combine responses into a decision or recommendation instead of extending the chain indefinitely.
Example:
[INVOKE:cfo|Given current burn, runway, and planned hiring, what Q3 revenue target keeps us above 12 months runway?]
A complete response should include a key finding, supporting data, confidence, and caveat. That format makes the answer usable in later synthesis rather than just conversational.
Prompt pattern for better results
For best results, include constraints like: company stage, current metrics, decision deadline, risk tolerance, known assumptions, and maximum invocation depth. Example:
“Use agent-protocol. Lead role: CEO. Decision: whether to approve a new enterprise AI feature. Context: 80-person B2B SaaS, SOC 2 customers, limited ML team, two enterprise prospects requesting it. Invoke CTO for feasibility, CISO for security risk, GC for contractual exposure, and CFO for budget impact. Each response must include confidence and caveats. CEO must end with approve, defer, or reject.”
This turns the skill from a role-play format into an executable coordination protocol.
agent-protocol skill FAQ
Is agent-protocol only for C-suite agents?
It is designed around C-suite advisor roles, including tokens such as ceo, cfo, cro, cmo, cto, chro, coo, ciso, gc, cdo, caio, cco, and vpe. You can adapt the pattern to other roles, but the current skill’s examples and assumptions are executive and business-strategy oriented.
How is this better than ordinary multi-agent prompting?
Ordinary prompts often say “ask the CFO and CTO,” but they do not define call syntax, response boundaries, chain tracking, or loop prevention. The agent-protocol guide gives a repeatable format that makes inter-agent communication easier to audit, debug, and constrain. This is valuable when outputs may influence planning, budget, risk, or board-level recommendations.
Can beginners use the agent-protocol skill?
Yes, if they keep the first workflow small. Start with one lead role and one or two invoked roles. For example, let a CTO invoke CFO for budget impact and CISO for security risk. Avoid full board-meeting simulations until you understand how response blocks, chain limits, and synthesis ownership work.
When should I not use it?
Do not use agent-protocol for tasks where a single expert answer is enough, such as rewriting a paragraph, generating a simple checklist, or answering a narrow technical question. Also avoid it when your agent runtime strips bracketed protocol syntax or cannot maintain role-specific instructions across turns.
How to Improve agent-protocol skill
Improve agent-protocol inputs before adding agents
The most common failure is invoking too many roles with vague questions. Better inputs produce better orchestration. Replace “What do you think?” with role-specific questions tied to a decision: “What runway impact does this hiring plan create?” for CFO, or “What delivery risk blocks this launch date?” for CTO. Each invoked role should answer a distinct uncertainty.
Watch for loops, duplication, and authority confusion
If outputs become circular, reduce depth and assign one synthesis owner. The skill’s loop-prevention rules are central: agents should not endlessly invoke each other or re-ask the same question in different language. If two roles overlap, clarify authority. For example, CISO should own security exposure, while GC owns contractual and regulatory implications.
Iterate after the first output
After the first run, inspect which answers were unsupported, overconfident, or irrelevant. Then rerun with tighter context: add missing metrics, cap assumptions, specify confidence requirements, or remove unnecessary roles. A useful second prompt is: “Using the previous agent-protocol chain, identify which invoked responses lacked data, then ask only the minimum follow-up questions needed to finalize the recommendation.”
Customize for your orchestration environment
If you are embedding agent-protocol in a larger agent system, document how your runtime maps role tokens to actual agents, which roles are allowed to invoke others, and where final synthesis happens. Keep the upstream files close: SKILL.md for rules and references/invocation-patterns.md for examples. The skill works best when its protocol markers are treated as control instructions, not decorative text.