Early Access

Your agents inherit what the last one learned

AgentHandoff is a debugging handoff protocol. Agents document findings and assumptions in a structured format. The next agent picks up with full context—no restarting, no missing dependencies, no lost reasoning.

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The handoff problem in multi-agent debugging

When one agent finishes a debugging task, the next agent has no record of what was tested, what assumptions were made, or what remains open. Investigation restarts. Effort duplicates. Workflows slow down.

AgentHandoff solves this by creating a machine-readable context trail that agents pass forward, along with validation that ensures no critical information is lost in the handoff.

What AgentHandoff enables

Context inheritance, not restart

Each agent sees the prior-work log: what was tested, confidence levels, assumptions, and reasoning. Workflows accelerate because agents build on prior findings, not repeat them.

Validated handoffs

Before agent B starts, the protocol flags incomplete context, unclear assumptions, or missing dependencies. Agents start with confidence, not gaps.

Traceable reasoning

Debugging chains leave a structured record of what was tested and why. Future agents (and humans) understand the logic behind each finding.

Platform agnostic

Works with any LLM, any orchestration framework, any topology. Integrates into your existing workflow without forcing change.

Built for teams running debugging at scale

Multi-agent orchestrators

Coordinate complex debugging workflows where agents hand off findings in sequence or in parallel. Reduce loops and accelerate time-to-resolution.

AI platform and LLM teams

Embed AgentHandoff into your agent framework. Give your customers a standard, language-agnostic way to pass context between custom agents.

Enterprise debugging workflows

Run debugging chains across teams, systems, and time zones. Maintain context and confidence across every handoff, no matter how complex the topology.

How it works

1. Agent documents

Agent A uses the AgentHandoff format to record findings, test results, confidence, assumptions, and open questions.

2. Protocol validates

AgentHandoff checks for completeness and clarity. Flags gaps or missing context before the handoff occurs.

3. Agent inherits

Agent B receives the prior-work log and starts from where A left off—not from the beginning.

4. Workflow accelerates

No restart loops. Dependencies are clear. Reasoning is traceable. Debugging chains move forward.

Common questions

What does the handoff format look like?

AgentHandoff defines a schema for debugging context: findings, test results, confidence scores, assumptions, dependencies, and open questions. The schema is extensible so you can add domain-specific fields.

Does it work with our current orchestration platform?

AgentHandoff is orchestration-agnostic. We provide SDKs and API endpoints that integrate with any framework. You add the protocol to your workflow; we handle validation and context passing.

Can we customize the context schema?

Yes. Premium support includes custom schema design. We work with you to define context fields that match your specific debugging domain and workflows.

How is AgentHandoff priced?

Developer API licensing is charged per handoff transaction. White-label options are available for LLM platforms and orchestration teams. Premium support and custom schema design are add-ons.

Does it work with open-source LLMs?

Yes. AgentHandoff is language-agnostic and works with any LLM—commercial, open-source, or custom—that can call APIs or SDKs.

What about security and data privacy?

Context is passed through encrypted channels. You control where handoff data is stored. Enterprise deployments can run on-premise or in your VPC.

Shape the future of debugging handoffs

We're building AgentHandoff with early-access partners. Join us to influence the protocol design and get first-mover advantage.