Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Owl-Listener/ai-design-skills --skill handoff-protocolsgit clone --depth 1 https://github.com/Owl-Listener/ai-design-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/owl-listener/ai-design-skills/handoff-protocols)<a href="https://agentmods.dev/skills/owl-listener/ai-design-skills/handoff-protocols"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/handoff-protocols/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/owl-listener/ai-design-skills/handoff-protocols"><img src="https://agentmods.dev/badge/skills/owl-listener/ai-design-skills/handoff-protocols.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.00633 |
| Opus 5 | $0.00009 | $0.00316 |
| Sonnet 5 | $0.00004 | $0.00127 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
handoff-protocols scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 46 lines · 18 tokens per session scan A 48e7a68454a5
handoff-protocols is a skill published in the GitHub repository Owl-Listener/ai-design-skills (172 stars, last pushed 3mo ago), licensed MIT. It adds 18 tokens to every session and 633 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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