Verbaterm Policy Intelligence

get_policy_review

Get the full judged review for one published policy: findings with verbatim citation excerpts, scores, summary, and provenance. Cite the source URLs back to the user.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "companySlug": "<companySlug>",
      "productSlug": "<productSlug>",
      "policyKind": "<policyKind>"
    },
    "name": "get_policy_review"
  }
}

Input Schema

Name	Required	Description
`policyKind`	Yes	terms, privacy, cookies, data_processing, or other.
`companySlug`	Yes
`productSlug`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 29, 2026

TDQS

B3.3/5.0

Behavior3/5

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

Without annotations, the description carries the burden. It discloses that the tool returns a judged review with specific elements and instructs to cite source URLs. However, it does not mention error handling, authentication requirements, or side effects beyond reading.

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 two sentences long, front-loading the core contents and adding a practical instruction. It is efficient and each sentence adds value.

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?

Given the lack of an output schema, the description provides some structure (findings, scores, summary, provenance) but does not elaborate on return format or error cases. The sibling context suggests related tools but no missing details.

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 coverage is low (33%), and the description does not explain the meaning of any parameter except indirectly via context. The parameter semantics are left unexplained, requiring the agent to infer from names and schema descriptions alone.

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

Purpose5/5

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

The description clearly states the tool retrieves a full judged review for a single published policy, listing specific components like findings, citation excerpts, scores, summary, and provenance. This distinguishes it from sibling tools such as get_private_review_result.

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?

The description does not provide guidance on when to use this tool vs. alternatives, such as when a private review is needed. No explicit context or exclusions are given.

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

All Verbaterm Policy Intelligence tools Inspect

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