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Agent Handoff Packet

agent_handoff_packet
Read-onlyIdempotent

Summarize current status and next steps in a compact handoff packet so another AI agent can continue SDLC work.

Instructions

Generate a compact handoff packet so another AI agent can continue SDLC work.

Use when wrapping up a session, before handing off to a specialised agent, or when context is nearing its limit.

Args:

  • owner, repo: Repository coordinates.

  • issueNumber (number?): Issue being worked on.

  • pullNumber (number?): PR being worked on.

  • currentStatus (string): What has been done so far.

  • nextSteps (string[]?): Ordered tasks for the next agent.

Returns: Compact handoff prompt, repo context snapshot, and remaining tasks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNoGitHub repo. Falls back to GITHUB_REPO.
ownerNoGitHub owner. Falls back to GITHUB_OWNER.
nextStepsNoOrdered list of next steps for the incoming agent.
pullNumberNoPR being worked on (if applicable).
issueNumberNoIssue being worked on (if applicable).
currentStatusYesFree-text description of the current work status.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYes
prRefYes
issueRefYes
nextStepsYes
policyDigestNo
currentStatusYes
defaultBranchYes
handoffPromptYes
policySourcesNo
policySummaryNo
policyDegradedNo
evidenceWarningsYes
appliedPolicyRulesNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that it generates a compact handoff packet and returns specific items, but doesn't elaborate on other behavioral aspects. It adds moderate value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with purpose and usage, followed by a clear parameter list. Slightly verbose with the 'Args:' and 'Returns:' sections, but well-structured and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and the presence of an output schema, the description covers all necessary aspects: purpose, when to use, parameters, and return value. No gaps or omissions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so schema already documents all parameters. The description lists each parameter with brief explanations, but these largely echo the schema descriptions. No significant additional meaning is added.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a handoff packet for AI agents to continue SDLC work. It distinguishes from siblings like plan_from_context and repo_context, which serve different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly specifies when to use: wrapping up a session, before handoff to a specialised agent, or when context is nearing its limit. This provides clear context and helps avoid misuse.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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