Skip to main content
Glama

product_predict

Destructive

Predict product outcomes by submitting a free-text objective and optional JSON inputs. Routes through your tenant, company, and JWT scope to run the product domain agent action.

Instructions

Run the product domain agent action predict.

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
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already carry destructiveHint=true and readOnlyHint=false, so the safety profile is partially covered. The description adds useful scoping context (JWT, tenant, company) and dispatcher routing, but it does not disclose that the underlying action may be destructive or what side effects it may trigger. No contradiction with annotations exists.

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 compact, front-loaded with the core action, and uses a clean Args list. Every sentence serves a purpose, and there is no filler or redundant content.

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 not required. However, the description leaves out selection criteria, side-effect expectations, and details about what makes a valid message or objective for the predict action. Given the destructive annotation, slightly more context would make the tool safer to invoke confidently.

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 does add meaning by labeling message as a free-text objective and inputs as an optional JSON string, but the guidance is terse and does not describe valid input shapes, expected keys, or how message and inputs interact.

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 states a specific verb ('Run') and resource ('product domain agent action predict') and clarifies that it goes through the platform's domain-agent dispatcher. It is not a tautology, but it does not explain what the 'predict' action actually produces or differentiate it from sibling tools like dispatch_domain_agent or commerce_predict.

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?

There is no guidance on when to use this tool versus alternatives, and no mention of when not to use it. The description only explains the internal routing mechanics and scope, not the decision context that would help an agent select this tool.

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

Deploy Server

Other Tools