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legal_tm_clearance_search

Destructive

Check trademark availability and identify potential conflicts by submitting your clearance objective. The legal domain agent processes the request and returns structured results.

Instructions

Run the legal domain agent action tm_clearance_search.

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

C2.8/5.0
Behavior3/5

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

Annotations already supply the destructive/open-world/idempotent profile, so the description was not required to restate it. It adds one useful behavioral detail: the operation routes through the domain-agent dispatcher under the caller's JWT/tenant/company scope, which explains the indirection and auth context. No explicit contradiction with the `destructiveHint: true` annotation exists, though the description does not explain what side effects may occur.

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 compact and front-loaded: it names the action first, then gives the routing context and argument definitions. Each sentence contributes, though a brief semantic explanation of the clearance search would make it more useful without hurting conciseness.

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 an agent choosing and invoking this tool, the description leaves important gaps: it never says what tm_clearance_search is for, what a valid `message` should contain, or how to populate `inputs`. The output schema lessens the need to document return values, but the invocation contract is still underspecified.

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 Args block adds minimal but real meaning beyond the schema: `message` is a free-text objective and `inputs` is an optional JSON string. It does not describe the expected structure of the JSON, acceptable values, or how message and inputs interact, so it only partially compensates for zero schema-description coverage.

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 names the exact action (`tm_clearance_search`) and identifies it as a legal-domain agent action, so the resource is identifiable. However, it never explains what a trademark clearance search actually does or what outcome the agent should expect, and it reads largely as a restatement of the tool name. It also does not differentiate from generic dispatcher siblings like `dispatch_domain_agent`.

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 about when to choose this tool over the many legal_* alternatives or `dispatch_domain_agent`. The only context is the routing/scoping sentence, which describes mechanics, not use cases or exclusions.

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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