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trust_check

Before delegating to or installing an AI agent, check its independent trust score, tier, and verdict. Returns evidence-backed assessment quickly.

Instructions

The core Hlido trust query: is a specific AI agent trustworthy? Given one agent (by Hlido slug or product/homepage URL) it returns the independent Laddoo trust score (0-100), tier (VITAL/STEADY/FADING/FLATLINE), a one-line verdict, a claim-verification summary, and any known incidents. Call this FIRST — before delegating to, installing, or relying on another agent — to get a fast trust read. Returns no_review_found if the agent isn't in Hlido's corpus (then call request_quick_audit). For the full claim-by-claim evidence, follow up with get_scorecard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_or_urlYesThe agent to check: either its Hlido slug (e.g. 'aider', 'cursor') or its product/homepage URL (e.g. 'https://cursor.com'). A URL is matched to the closest reviewed agent.
use_caseNoOptional. The task you're considering this agent for (e.g. 'multi-file TypeScript refactor'); tailors the verdict to that use case when provided.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.1
    • addedInput schema / properties / agent_or_url / description
      Added value: +"The agent to check: either its Hlido slug (e.g. 'aider', 'cursor') or its product/homepage URL (e.g. 'https://cursor.com'). A URL is matched to the closest reviewed agent."
    • addedInput schema / properties / use_case / description
      Added value: +"Optional. The task you're considering this agent for (e.g. 'multi-file TypeScript refactor'); tailors the verdict to that use case when provided."
  2. First observedv0.1.0

TDQS

A4.7/5.0
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 details return values (score, tier, verdict, summary, incidents), the no_review_found error case, and the quick nature of the query. It lacks explicit read-only confirmation or rate limits but provides substantial behavioral context beyond the schema.

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?

Three sentences, front-loaded with purpose, then usage guidance, then error handling and follow-up. Every sentence earns its place with no repetition or filler.

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?

Despite no output schema or annotations, the description covers core functionality, expected outputs, error condition, and alternatives. The tool is simple (2 params, no nested objects), and the description provides all needed invocation context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds meaning: it clarifies agent_or_url accepts a Hlido slug or product URL and that URLs are matched to the closest reviewed agent. It also explains that use_case tailors the verdict, enriching the schema definitions.

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 states a specific verb ('returns') and resource ('the independent Laddoo trust score, tier, verdict, claim-verification summary, incidents'), and clearly distinguishes itself from siblings by positioning as 'the core Hlido trust query' and naming alternatives like get_scorecard and request_quick_audit for follow-up use cases.

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

Usage Guidelines5/5

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

Explicitly instructs when to call: 'Call this FIRST — before delegating to, installing, or relying on another agent'. It also provides exclusions and alternatives: if no_review_found, 'then call request_quick_audit', and for full evidence, 'follow up with get_scorecard'.

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