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Codex CLI
Muse
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Grok Bot+18 agentsMulti-Agent Handoff Architect
Design reliable multi-agent workflows with clear roles, handoff contracts, shared context, state management, approval gates, retries, escalation rules, and failure-safe coordination.
$8
Multi-Agent Handoff Architect
Example session with this skill installed
I want to build a multi-agent system for an AI marketing agency.
Current workflow
-
Research Agent
Researches competitors, market trends, products, and customer insights. -
Strategy Agent
Turns research into campaign strategy. -
Copywriting Agent
Creates headlines, captions, ad copy, and CTA variations. -
Visual Prompt Agent
Creates image and video generation prompts. -
QA Agent
Reviews copy and creative prompts before delivery. -
Client Delivery Agent
Prepares the final deliverable for the client.
Problems I want to avoid
• Agents losing context between steps
• The Strategy Agent making decisions when research quality is poor
• The Copywriting Agent inventing information not found in research
• QA sending work backward forever
• Duplicate responsibilities
• Agents rewriting each other's work unnecessarily
• Client-facing output being delivered without final approval
Design the full multi-agent handoff architecture.
Include
• Agent responsibilities
• What each agent can and cannot do
• Input and output contracts
• Required context for each handoff
• Confidence thresholds
• Validation gates
• Retry rules
• Escalation logic
• Human approval points
• State transitions
• Failure conditions
• Termination rules
• Recommended workflow order
I want the system to be practical enough to implement later in an agent framework.
- Read your context and instructions
- Compiled the multi-agent handoff architect
- Generated the UI component
Multi-Agent Handoff Blueprint
Executive Architecture
The proposed workflow should use a controlled sequential pipeline with conditional return paths rather than unrestricted agent-to-agent delegation.
Recommended architecture
Research
→ Research Validation
→ Strategy
→ Strategy Validation
→ Copy + Visual Prompt Production
→ QA
→ Human Approval
→ Client Delivery
The main architectural principle is
NO DOWNSTREAM AGENT SHOULD CONTINUE WHEN ITS REQUIRED INPUT CONTRACT IS INVALID.
This prevents weak research from contaminating every later stage.
Agent Map
Agent 01 — Research Agent
Responsibility
Collect and structure verified market, competitor, product, and customer information.
Can
• Research approved sources
• Extract facts
• Compare competitors
• Identify patterns
• Summarize evidence
• Assign confidence
Cannot
• Decide final campaign strategy
• Invent unsupported customer insights
• Write final campaign copy
• Approve its own research quality
Required Output
ResearchPackage
Must contain
• research_objective
• findings
• competitors
• customer_insights
• verified_claims
• source_references
• uncertainties
• confidence_score
Exit Gate
Proceed only if
confidence_score >= 0.75
and
all critical claims have supporting evidence.
If confidence < 0.75:
RETURN TO RESEARCH.
Handoff 01
Research Agent
→ Strategy Agent
Handoff Contract
Required fields
research_summary
verified_claims
competitor_findings
audience_findings
sources
uncertainties
confidence_score
Validation
The Strategy Agent must reject the handoff when:
• research confidence is below threshold
• critical source fields are missing
• unsupported claims are present
• target audience information is insufficient
The Strategy Agent must not repair missing research by inventing assumptions.
Agent 02 — Strategy Agent
Responsibility
Convert validated research into campaign strategy.
Can
• Define campaign objective
• Develop positioning
• Choose messaging angles
• Prioritize customer pain points
• Define content structure
Cannot
• Introduce unsupported market claims
• Modify verified research facts
• Generate final copy
• Approve its own strategy
Required Output
StrategyPackage
Contains
• campaign_objective
• target_audience
• positioning
• core_message
• proof_points
• creative_angles
• content_requirements
• prohibited_claims
• confidence_score
Exit Gate
Proceed when
strategy completeness = PASS
and
confidence_score >= 0.80
Handoff 02
Strategy Agent
→ Copywriting Agent
and
→ Visual Prompt Agent
This handoff may branch in parallel.
Both agents receive the same approved StrategyPackage.
They must not receive the entire raw research history unless required.
This reduces context overload.
Agent 03 — Copywriting Agent
Responsibility
Create campaign copy from approved strategy.
Can
• Write headlines
• Captions
• CTA variants
• Ad copy
Cannot
• Introduce new factual claims
• Change positioning
• Create unsupported statistics
• Override strategy constraints
Output Contract
CopyPackage
• headline_variants
• body_copy
• captions
• CTA
• claims_used
• strategy_reference
Agent 04 — Visual Prompt Agent
Responsibility
Translate strategy into production-ready visual prompts.
Can
• Define visual concept
• Camera direction
• Scene
• Lighting
• Composition
• Prompt structure
Cannot
• Alter factual product attributes
• Introduce unsupported product claims
• Rewrite campaign strategy
Output Contract
VisualPackage
• concept
• image_prompts
• video_prompts
• visual_constraints
• product_consistency_rules
• strategy_reference
Synchronization Gate
CopyPackage
+
VisualPackage
↓
QA Agent
QA must wait until both packages are complete.
Partial execution is not allowed.
Agent 05 — QA Agent
Responsibility
Validate consistency, quality, compliance, and cross-agent alignment.
QA Checks
• Copy matches strategy
• Visual direction matches strategy
• Claims trace to approved research
• No prohibited claims
• No contradiction between copy and visual
• Required deliverables are complete
QA Decision
PASS
REVISE_COPY
REVISE_VISUAL
REVISE_STRATEGY
ESCALATE_HUMAN
Retry Architecture
Maximum automatic retries per stage
2
Example
QA
→ REVISE_COPY
→ Copywriting Agent
→ QA
If the same failure occurs twice
ESCALATE TO HUMAN.
This prevents infinite revision loops.
Rework Rules
Do not send work farther upstream than necessary.
Example
Typography problem
QA
→ Visual Prompt Agent
Do NOT
QA
→ Strategy
→ Research
Unsupported marketing claim
QA
→ Strategy
Potentially false source data
QA
→ Research
Use the lowest-cost valid rework path.
Human Approval Gate
After QA PASS
QA
→ HUMAN APPROVAL
Human reviewer validates
• Client suitability
• Brand judgment
• Sensitive claims
• Strategic quality
• Commercial readiness
Only after
HUMAN_APPROVED = TRUE
can the Client Delivery Agent execute.
Agent 06 — Client Delivery Agent
Responsibility
Package approved assets for delivery.
Can
• Format deliverables
• Organize files
• Create delivery summary
• Prepare client-facing package
Cannot
• Change approved copy
• Change strategy
• Add claims
• Bypass human approval
Start Condition
QA_STATUS = PASS
AND
HUMAN_APPROVED = TRUE
Otherwise
STOP.
Workflow State Model
Possible states
RESEARCHING
RESEARCH_VALIDATION
STRATEGY
STRATEGY_VALIDATION
PRODUCTION
QA
REWORK
HUMAN_REVIEW
APPROVED
DELIVERY
COMPLETED
ESCALATED
FAILED
Every workflow instance should have exactly one current state.
Context Architecture
Use three context levels.
Global Context
Shared across the entire workflow
• client identity
• campaign objective
• product facts
• brand rules
• prohibited claims
Stage Context
Only information required for the current agent.
Handoff Payload
Structured output from the previous stage.
Avoid forwarding entire conversation histories between every agent.
Confidence Architecture
Research Agent
minimum 0.75
Strategy Agent
minimum 0.80
QA
must explicitly PASS.
Confidence alone should not authorize high-risk actions.
Failure Conditions
Stop or escalate when
• required source data is missing
• unsupported claims persist
• agent output violates contract
• repeated QA failure exceeds retry limit
• conflicting product information exists
• mandatory human approval is missing
• client requirements contradict internal policy
Termination Conditions
SUCCESS
All deliverables approved and delivery completed.
ESCALATED
Human decision required.
FAILED
Workflow cannot continue safely.
Never allow the system to continue indefinitely.
Responsibility Matrix
| Activity | Research | Strategy | Copy | Visual | QA | Human | Delivery |
|---|---|---|---|---|---|---|---|
| Research facts | OWN | Read | Read | Read | Verify | Review | — |
| Strategy | — | OWN | Follow | Follow | Verify | Review | — |
| Copy | — | — | OWN | — | Review | Approve | Package |
| Visual prompts | — | — | — | OWN | Review | Approve | Package |
| Quality control | — | — | — | — | OWN | Override | — |
| Final approval | — | — | — | — | Recommend | OWN | — |
| Delivery | — | — | — | — | — | Authorize | OWN |
Recommended Workflow
Research Agent
↓
Research Validation
↓
Strategy Agent
↓
Strategy Validation
↓
┌────────────────────┐
Copy Agent Visual Agent
└──────────┬─────────┘
↓
Synchronization
↓
QA Agent
↓
PASS / REWORK
↓
Human Approval
↓
Client Delivery
↓
COMPLETED
Primary Architecture Insight
MULTI-AGENT SYSTEMS SHOULD NOT BE DESIGNED AS:
“AGENT A TALKS TO AGENT B.”
They should be designed as
ROLE
+
CONTRACT
+
STATE
+
VALIDATION
+
ROUTING
+
FAILURE HANDLING
+
HUMAN CONTROL
The handoff architecture is what turns a collection of agents into a reliable system.
multi-agent-handoff-architect.tsx
TSX · React component
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
Multi-Agent Handoff Architect designs reliable coordination systems for workflows that use multiple AI agents, tools, and human reviewers.
Many multi-agent systems fail not because individual agents are weak, but because responsibilities are unclear, context is lost between steps, outputs are inconsistent, retry logic is missing, or agents do not know when to stop, escalate, or return work upstream.
This skill turns a multi-step business or AI workflow into a structured handoff architecture.
It can design
- Agent roles and responsibility boundaries
- Agent-to-agent handoffs
- Human approval checkpoints
- Input and output contracts
- Shared context requirements
- Structured handoff payloads
- State transitions
- Confidence thresholds
- Validation gates
- Retry logic
- Escalation paths
- Failure handling
- Rework loops
- Termination conditions
- Parallel-agent workflows
- Sequential-agent workflows
- Supervisor and router patterns
- Quality-control agents
- Human-in-the-loop systems
For every agent, the skill defines what information it receives, what it is responsible for, what it must return, what it must never decide, and what conditions allow the workflow to continue.
The skill also identifies dangerous coordination patterns such as duplicated responsibility, circular delegation, context overload, ambiguous ownership, premature execution, uncontrolled retries, missing approval gates, and agents acting on low-confidence outputs.
Multi-Agent Handoff Architect can transform an existing agent workflow into a more reliable architecture or design a multi-agent system from scratch.
The final deliverable can include an agent map, responsibility matrix, handoff contracts, state model, routing logic, confidence rules, approval gates, retry and escalation architecture, failure-mode analysis, and implementation-ready workflow specification.
Designed for AI builders, automation agencies, developers, consultants, product teams, operations teams, and businesses building agentic workflows with multiple specialized AI agents.
Multi-Agent Handoff Architect designs coordination architecture. It does not automatically deploy agents, configure external systems, or guarantee production reliability.
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