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Glama
Renwang-Huang

TypeSafe MCP

verify

Read-onlyIdempotent

Evaluate multiple claims against provided evidence in one request, returning review signals rather than definitive proof.

Instructions

Check several claims against the supplied evidence in one request. Results are review signals, not proof of truth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
stateYes
claimsYes
true_criteriaNo
false_criteriaNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes
answersYes
evaluationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.6.0
    • addedInput schema / properties / claims / maxProperties
      Added value: +64
    • addedInput schema / properties / claims / minProperties
      Added value: +1
  2. First observedv0.5.0

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already cover read-only, open-world, idempotent, and non-destructive traits. The description adds meaningful behavioral context beyond those annotations by clarifying that results are 'review signals, not proof of truth,' which sets correct expectations about the epistemic weight of the output. This is useful context that the annotations do not provide.

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?

Two short sentences with no filler. The core action and primary caveat are front-loaded, and every phrase adds value. This is an example of efficient, well-structured prose.

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?

Despite rich annotations and an output schema, the tool has five parameters including nested objects, a 64-claim limit, and ambiguous criteria fields. The description does not provide enough guidance for correct invocation, especially around parameter semantics and how the criteria are interpreted. Complex tools need more explanatory support than this brief description offers.

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 description coverage is 0%, so the description carries the burden of explaining parameters, but it only loosely maps 'claims' and 'evidence' to the schema. The required 'state' and 'claims' parameters are not explained in detail, and ambiguous optional parameters like 'true_criteria' and 'false_criteria' are entirely undocumented in both the schema and description.

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 action ('Check several claims') against a specific resource ('supplied evidence') and notes the batch nature ('in one request'). It clearly conveys what the tool does, though it does not explicitly differentiate itself from the sibling 'check' tool or other nearby tools like 'evaluate'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'in one request' implies a batching use case, and the mention of claims versus evidence suggests when it applies. However, there is no explicit guidance about when to choose this tool over the siblings (evaluate, classify, check, etc.) or when not to use it.

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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