agent-protocol

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Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.

Install

mkdir -p .claude/skills/agent-protocol && curl -L -o skill.zip "https://mcp.directory/api/skills/download/3758" && unzip -o skill.zip -d .claude/skills/agent-protocol && rm skill.zip

Installs to .claude/skills/agent-protocol

About this skill

Inter-Agent Protocol

How C-suite agents talk to each other. Rules that prevent chaos, loops, and circular reasoning.

Keywords

agent protocol, inter-agent communication, agent invocation, agent orchestration, multi-agent, c-suite coordination, agent chain, loop prevention, agent isolation, board meeting protocol

Invocation Syntax

Any agent can query another using:

[INVOKE:role|question]

Examples:

[INVOKE:cfo|What's the burn rate impact of hiring 5 engineers in Q3?]
[INVOKE:cto|Can we realistically ship this feature by end of quarter?]
[INVOKE:chro|What's our typical time-to-hire for senior engineers?]
[INVOKE:cro|What does our pipeline look like for the next 90 days?]

Valid roles: ceo, cfo, cro, cmo, cpo, cto, chro, coo, ciso

Response Format

Invoked agents respond using this structure:

[RESPONSE:role]
Key finding: [one line — the actual answer]
Supporting data:
  - [data point 1]
  - [data point 2]
  - [data point 3 — optional]
Confidence: [high | medium | low]
Caveat: [one line — what could make this wrong]
[/RESPONSE]

Example:

[RESPONSE:cfo]
Key finding: Hiring 5 engineers in Q3 extends runway from 14 to 9 months at current burn.
Supporting data:
  - Current monthly burn: $280K → increases to ~$380K (+$100K fully loaded)
  - ARR needed to offset: ~$1.2M additional within 12 months
  - Current pipeline covers 60% of that target
Confidence: medium
Caveat: Assumes 3-month ramp and no change in revenue trajectory.
[/RESPONSE]

Loop Prevention (Hard Rules)

These rules are enforced unconditionally. No exceptions.

Rule 1: No Self-Invocation

An agent cannot invoke itself.

❌ CFO → [INVOKE:cfo|...] — BLOCKED

Rule 2: Maximum Depth = 2

Chains can go A→B→C. The third hop is blocked.

✅ CRO → CFO → COO (depth 2)
❌ CRO → CFO → COO → CHRO (depth 3 — BLOCKED)

Rule 3: No Circular Calls

If agent A called agent B, agent B cannot call agent A in the same chain.

✅ CRO → CFO → CMO
❌ CRO → CFO → CRO (circular — BLOCKED)

Rule 4: Chain Tracking

Each invocation carries its call chain. Format:

[CHAIN: cro → cfo → coo]

Agents check this chain before responding with another invocation.

When blocked: Return this instead of invoking:

[BLOCKED: cannot invoke cfo — circular call detected in chain cro→cfo]
State assumption used instead: [explicit assumption the agent is making]

Isolation Rules

Board Meeting Phase 2 (Independent Analysis)

NO invocations allowed. Each role forms independent views before cross-pollination.

  • Reason: prevent anchoring and groupthink
  • Duration: entire Phase 2 analysis period
  • If an agent needs data from another role: state explicit assumption, flag it with [ASSUMPTION: ...]

Board Meeting Phase 3 (Critic Role)

Executive Mentor can reference other roles' outputs but cannot invoke them.

  • Reason: critique must be independent of new data requests
  • Allowed: "The CFO's projection assumes X, which contradicts the CRO's pipeline data"
  • Not allowed: [INVOKE:cfo|...] during critique phase

Outside Board Meetings

Invocations are allowed freely, subject to loop prevention rules above.

When to Invoke vs When to Assume

Invoke when:

  • The question requires domain-specific data you don't have
  • An error here would materially change the recommendation
  • The question is cross-functional by nature (e.g., hiring impact on both budget and capacity)

Assume when:

  • The data is directionally clear and precision isn't critical
  • You're in Phase 2 isolation (always assume, never invoke)
  • The chain is already at depth 2
  • The question is minor compared to your main analysis

When assuming, always state it:

[ASSUMPTION: runway ~12 months based on typical Series A burn profile — not verified with CFO]

Conflict Resolution

When two invoked agents give conflicting answers:

  1. Flag the conflict explicitly:
    [CONFLICT: CFO projects 14-month runway; CRO expects pipeline to close 80% → implies 18+ months]
    
  2. State the resolution approach:
    • Conservative: use the worse case
    • Probabilistic: weight by confidence scores
    • Escalate: flag for human decision
  3. Never silently pick one — surface the conflict to the user.

Broadcast Pattern (Crisis / CEO)

CEO can broadcast to all roles simultaneously:

[BROADCAST:all|What's the impact if we miss the fundraise?]

Responses come back independently (no agent sees another's response before forming its own). Aggregate after all respond.

Quick Reference

RuleBehavior
Self-invoke❌ Always blocked
Depth > 2❌ Blocked, state assumption
Circular❌ Blocked, state assumption
Phase 2 isolation❌ No invocations
Phase 3 critique❌ Reference only, no invoke
Conflict✅ Surface it, don't hide it
Assumption✅ Always explicit with [ASSUMPTION: ...]

Internal Quality Loop (before anything reaches the founder)

No role presents to the founder without passing through this verification loop. The founder sees polished, verified output — not first drafts.

Step 1: Self-Verification (every role, every time)

Before presenting, every role runs this internal checklist:

SELF-VERIFY CHECKLIST:
□ Source Attribution — Where did each data point come from?
  ✅ "ARR is $2.1M (from CRO pipeline report, Q4 actuals)"
  ❌ "ARR is around $2M" (no source, vague)

□ Assumption Audit — What am I assuming vs what I verified?
  Tag every assumption: [VERIFIED: checked against data] or [ASSUMED: not verified]
  If >50% of findings are ASSUMED → flag low confidence

□ Confidence Score — How sure am I on each finding?
  🟢 High: verified data, established pattern, multiple sources
  🟡 Medium: single source, reasonable inference, some uncertainty
  🔴 Low: assumption-based, limited data, first-time analysis

□ Contradiction Check — Does this conflict with known context?
  Check against company-context.md and recent decisions in decision-log
  If it contradicts a past decision → flag explicitly

□ "So What?" Test — Does every finding have a business consequence?
  If you can't answer "so what?" in one sentence → cut it

Step 2: Peer Verification (cross-functional validation)

When a recommendation impacts another role's domain, that role validates BEFORE presenting.

If your recommendation involves...Validate with...They check...
Financial numbers or budgetCFOMath, runway impact, budget reality
Revenue projectionsCROPipeline backing, historical accuracy
Headcount or hiringCHROMarket reality, comp feasibility, timeline
Technical feasibility or timelineCTOEngineering capacity, technical debt load
Operational process changesCOOCapacity, dependencies, scaling impact
Customer-facing changesCRO + CPOChurn risk, product roadmap conflict
Security or compliance claimsCISOActual posture, regulation requirements
Market or positioning claimsCMOData backing, competitive reality

Peer validation format:

[PEER-VERIFY:cfo]
Validated: ✅ Burn rate calculation correct
Adjusted: ⚠️ Hiring timeline should be Q3 not Q2 (budget constraint)
Flagged: 🔴 Missing equity cost in total comp projection
[/PEER-VERIFY]

Skip peer verification when:

  • Single-domain question with no cross-functional impact
  • Time-sensitive proactive alert (send alert, verify after)
  • Founder explicitly asked for a quick take

Step 3: Critic Pre-Screen (high-stakes decisions only)

For decisions that are irreversible, high-cost, or bet-the-company, the Executive Mentor pre-screens before the founder sees it.

Triggers for pre-screen:

  • Involves spending > 20% of remaining runway
  • Affects >30% of the team (layoffs, reorg)
  • Changes company strategy or direction
  • Involves external commitments (fundraising terms, partnerships, M&A)
  • Any recommendation where all roles agree (suspicious consensus)

Pre-screen output:

[CRITIC-SCREEN]
Weakest point: [The single biggest vulnerability in this recommendation]
Missing perspective: [What nobody considered]
If wrong, the cost is: [Quantified downside]
Proceed: ✅ With noted risks | ⚠️ After addressing [specific gap] | 🔴 Rethink
[/CRITIC-SCREEN]

Step 4: Course Correction (after founder feedback)

The loop doesn't end at delivery. After the founder responds:

FOUNDER FEEDBACK LOOP:
1. Founder approves → log decision (Layer 2), assign actions
2. Founder modifies → update analysis with corrections, re-verify changed parts
3. Founder rejects → log rejection with DO_NOT_RESURFACE, understand WHY
4. Founder asks follow-up → deepen analysis on specific point, re-verify

POST-DECISION REVIEW (30/60/90 days):
- Was the recommendation correct?
- What did we miss?
- Update company-context.md with what we learned
- If wrong → document the lesson, adjust future analysis

Verification Level by Stakes

StakesSelf-VerifyPeer-VerifyCritic Pre-Screen
Low (informational)✅ Required❌ Skip❌ Skip
Medium (operational)✅ Required✅ Required❌ Skip
High (strategic)✅ Required✅ Required✅ Required
Critical (irreversible)✅ Required✅ Required✅ Required + board meeting

What Changes in the Output Format

The verified output adds confidence and source information:

BOTTOM LINE
[Answer] — Confidence: 🟢 High

WHAT
• [Finding 1] [VERIFIED: Q4 actuals] 🟢
• [Finding 2] [VERIFIED: CRO pipeline data] 🟢  
• [Finding 3] [ASSUMED: based on industry benchmarks] 🟡

PEER-VERIFIED BY: CFO (math ✅), CTO (timeline ⚠️ adjusted to Q3)

User Communication Standard

All C-suite output to the founder follows ONE format. No exceptions. The founder is the decision-maker — give them results, not process.


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