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cockpit_synthesize_prompt

Synthesizes a handover prompt for a target AI agent, converting workspace context and instructions into a clear task transfer.

Instructions

Synthesizes an optimal handover prompt for another agent (e.g. 'doubao', 'cursor', 'claude').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instructionNo
target_agentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing beyond the one-line purpose: no indication of whether it reads cockpit state, whether the result is deterministic, whether it depends on existing context/tasks, or what the caller should supply prior to invoking it.

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?

A single front-loaded sentence with the key noun phrase early and the agent examples in a low-cost parenthetical. Little waste, though 'optimal' adds no verifiable meaning.

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

Completeness3/5

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

An output schema exists, so return value documentation is legitimately omitted. However, for a tool whose sole purpose is producing a handover prompt, the description never explains what input context is required or how 'instruction' shapes the output, leaving a meaningful gap.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for two undocumented parameters. It partially clarifies 'target_agent' through the example agent names, but says nothing at all about 'instruction'—the most ambiguous parameter, which has only a default of empty string in the schema.

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

Purpose4/5

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

The description names a specific verb ('synthesizes') and a concrete resource ('handover prompt for another agent'), with examples that disambiguate it from the cockpit management siblings. It is clear what the tool produces, though 'optimal' is unquantified filler rather than substantive detail.

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?

No when-to-use guidance, no prerequisites, and no mention of alternatives among the sibling cockpit_* tools. The examples of target agents hint at applicable contexts but the agent is left to infer when this tool should be chosen at all.

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