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handoff_merge

Merge multiple conversation handoffs into a single unified record, combining conversations and metadata from related handoffs for consolidated management.

Instructions

Merge multiple handoffs into one. Combines conversations and metadata from related handoffs into a single unified handoff.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keysYesKeys of the handoffs to merge (minimum 2)
new_keyNoKey for the merged handoff. Auto-generated if omitted.
new_titleNoTitle for the merged handoff. Auto-generated if omitted.
new_summaryNoSummary for the merged handoff. Auto-generated from source summaries if omitted.
delete_sourcesNoWhether to delete source handoffs after merging
strategyNoMerge strategy: 'chronological' sorts by creation time, 'sequential' keeps array orderchronological
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions merging and combining data but lacks critical details: whether this is a destructive operation (implied by 'merge' but not explicit), permission requirements, error handling, or what happens to source handoffs (only hinted at in the schema via 'delete_sources'). This leaves significant gaps for a mutation tool.

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

Conciseness5/5

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

The description is two sentences with zero waste, front-loading the core action ('merge multiple handoffs into one') and efficiently detailing the scope ('combines conversations and metadata'). Every word contributes directly to understanding the tool's function.

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

Completeness2/5

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

For a mutation tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral context (e.g., side effects, error cases), output details, and usage guidance, relying solely on the schema for parameter info. This is inadequate given the tool's complexity and potential impact.

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 the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't explain why merging is needed or how parameters interact). Baseline 3 is appropriate since the schema does the heavy lifting.

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 specific action ('merge multiple handoffs into one') and the resources involved ('handoffs'), distinguishing it from sibling tools like handoff_list or handoff_load. It specifies what gets combined ('conversations and metadata') and the outcome ('single unified handoff'), providing a precise purpose.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like handoff_clear or handoff_save, nor does it mention prerequisites or exclusions. It states what the tool does but offers no context for decision-making, leaving usage entirely implicit.

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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