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product_experiment_design

Design product experiments by specifying a free-text objective. Optionally provide structured inputs for the experiment.

Instructions

Run the product domain agent action experiment_design.

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?

No annotations are provided, so the description carries the full burden. It discloses that the tool routes through a dispatcher under JWT, tenant, and company scope, giving some behavioral context. However, it doesn't disclose destructive potential, rate limits, or success/failure conditions.

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

Conciseness3/5

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

The description is short but includes routing details that may be unnecessary. It is front-loaded with purpose, but the length is adequate, not excellent.

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?

Given the tool has two parameters and an output schema, the description covers the basics but omits what the action actually does, expected behavior, and when to use it. The output schema might describe return values, but context beyond parameters is lacking.

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 0%, so the description must compensate. It briefly explains 'message' as a free-text objective and 'inputs' as an optional JSON string. This adds meaning beyond the schema's default values but lacks detail on format or examples.

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

Purpose3/5

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

The description states 'Run the product domain agent action experiment_design' which gives a specific verb and resource, but it doesn't clarify what experiment_design entails. It distinguishes from siblings only by naming the action, but without context on what it does, the clarity is limited.

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 on when to use this tool vs. alternatives. With siblings like product_experimentation, the agent needs differentiation criteria, but the description provides none.

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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