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product_feedback_synthesis

Synthesize product feedback by specifying an objective and optional structured inputs. Generates actionable insights from feedback data.

Instructions

Run the product domain agent action feedback_synthesis.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
inputsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the burden. It discloses routing via domain-agent dispatcher under JWT, tenant, and company scope, which provides some transparency. However, it does not describe side effects, performance implications, or whether the tool is read-only or mutating.

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 succinct with four sentences. It gets directly to the point without fluff, though the implementation detail about routing could be omited for conciseness.

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?

For a tool with 2 optional params and an output schema, the description provides the basic usage but does not elaborate on the action's purpose or output. The output schema exists but is not referenced in the description, leaving an information gap.

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?

The description adds basic meaning to both parameters ('Free-text objective' and 'Optional JSON string of structured inputs'), compensating for the 0% schema description coverage. However, the descriptions are minimal and lack format details, examples, or constraints.

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 clearly states the tool runs a specific domain agent action named 'feedback_synthesis', providing a clear verb+resource combination. However, it does not explain what the action does or distinguish it from other similar tools.

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 guidance is provided on when to use this tool versus alternatives, no prerequisites, and no exclusions. The description only states the mechanism without contextual usage advice.

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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