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ankitkapur1992-hlido

hlido-mcp

by ankitkapur1992-hlido
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JavaScript
Hybrid

verify_claim

Fact-check a vendor's specific claim about an AI agent using Hlido's independent tests. Get a clear verdict with quoted evidence to validate promises before relying on them.

Instructions

Fact-check one specific marketing or capability claim about an agent against Hlido's independent testing. Returns Hlido's verdict (PASS/FAIL/PARTIAL/UNKNOWN) with a quoted evidence snippet and its source surface — or an honest null when that exact claim wasn't tested (absence of evidence, not proof). Use this to validate a vendor's specific promise before you rely on it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentYesThe agent's Hlido slug or product URL (e.g. 'cursor').
claimYesThe specific claim to verify, in plain language (e.g. 'works offline' or 'SOC 2 compliant').

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.1
    • addedInput schema / properties / agent / description
      Added value: +"The agent's Hlido slug or product URL (e.g. 'cursor')."
    • addedInput schema / properties / claim / description
      Added value: +"The specific claim to verify, in plain language (e.g. 'works offline' or 'SOC 2 compliant')."
  2. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the verdict values (PASS/FAIL/PARTIAL/UNKNOWN), the evidence snippet with source, and the honest null case with its meaning. It stops short of discussing permissions or side effects, but for a read-only fact-check this is adequate.

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 dense sentences: the first states purpose, the second explains return behavior and when to use. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Since there is no output schema, the description must explain return values, and it does: verdict values, quoted evidence, source surface, and the null case. For a two-parameter tool, this is fully complete.

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 schema already covers both parameters 100%, so the description adds little beyond the claim should be specific and in plain language—which the schema also says. Baseline 3 is appropriate.

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 uses the specific verb 'fact-check' and identifies the resource: one marketing/capability claim about an agent, tested against Hlido's independent testing. This clearly distinguishes it from broader tools like verify_transparency or trust_check.

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

Usage Guidelines4/5

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

It provides clear context: 'Use this to validate a vendor's specific promise before you rely on it.' However, it does not explicitly name alternative tools or state when not to use it, so it is not a full 5.

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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