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handoff-protocols

handoff-protocols

github.com/owl-listenerAgent workflows191145 installsUpdated 20w ago
Repository

About handoff-protocols

handoff-protocols is a skill for designing agent-to-agent and agent-to-human handoffs. It covers handoff flows, context transfer, user experience, failure modes, and design artefacts.

Key features

  1. 01Handoff triggers, sources, destinations, and acknowledgments
  2. 02Sequential, parallel, escalation, and fallback handoffs
  3. 03Context transfer approaches
  4. 04User-facing handoff experience patterns
  5. 05Failure modes and design artefacts

Use cases

  1. 01Specifying when and how agents pass tasks
  2. 02Designing context payloads for agent transitions
  3. 03Planning user-visible handoffs or escalations
  4. 04Reviewing handoffs for lost context or stalled work

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/owl-listener/ai-design-skills --skill handoff-protocols

After installing, type/handoff-protocolsin Claude Code to confirm it loaded.

Details

From the project README

Handoff Protocols

A handoff is the moment one agent passes work to another — or to a human. It's where multi-agent systems most commonly fail. A dropped handoff means lost context, repeated work, or abandoned tasks.

Anatomy of a Handoff

Every handoff has:

  • Trigger: What causes the handoff? (task completion, scope boundary, failure, user request)
  • Source: Who is handing off?
  • Destination: Who is receiving?
  • Payload: What information transfers? (context, partial results, user state, instructions)
  • Acknowledgment: How does the source know the destination received the handoff?
  • User experience: What does the user see during the handoff?

Handoff Types

  • Sequential: Agent A finishes, passes results to Agent B who continues. Like a relay race.
  • Parallel fan-out: One agent distributes subtasks to multiple agents simultaneously.
  • Parallel fan-in: Multiple agents' results converge back to one agent for synthesis.
  • Escalation: An agent can't handle the task and passes up to a more capable agent or human.
  • Fallback: The primary agent fails and a backup takes over.
  • Human handoff: AI passes work to a human for review, decision, or completion.

Context Transfer

The most common handoff failure is context loss. Design what transfers:

  • Full context: Everything the source agent knew. Safe but potentially overwhelming.
  • Summarised context: Key information distilled. Efficient but risks losing important nuance.
  • Structured context: Predefined fields that must be populated. Consistent but rigid.
  • Incremental context: Only what's new since the last handoff. Efficient for ongoing collaborations.

Designing for the User

The user's experience of handoffs matters:

  • Invisible handoff: The user doesn't know agents changed. The experience feels seamless.
  • Transparent handoff: The user is told a new agent is taking over and why.
  • Participatory handoff: The user confirms the handoff or provides additional context.
  • User-initiated handoff: The user explicitly requests a different agent or a human.

Handoff Anti-Patterns

  • The black hole: Work is handed off but never picked up
  • The echo chamber: Agents hand work back and forth without progress
  • The context cliff: Critical information is lost in the handoff
  • The jarring transition: The user's experience changes dramatically at the handoff point
  • The silent redirect: The user doesn't know they've been handed off and gets confused by changes

Design Artefacts

  • Handoff protocol specifications (trigger, source, destination, payload, acknowledgment)
  • Context transfer templates
  • Handoff sequence diagrams
  • User experience specifications for each handoff type
  • Handoff failure mode analysis

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