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Trust Engine MCP

Trust Engine MCP

by DinevDecor
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

pricing

Retrieve published Trust Engine AI prices in US$ valid from 12 Nov 2026, including free pilot, fixed-price 7-day test, audits, monitoring, and add-ons, with order and terms links.

Instructions

Use when asked what Trust Engine AI costs: published prices in US$, valid from 12 Nov 2026 (free pilot, fixed-price 7-day test, diet audit, re-test, 24/7 watch on your tasks, Bulgarian review, pay-from-savings option, add-ons), with order and terms links. For a fast fixed-price answer: the 7-day test.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "pricing"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
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 currency (US$), a validity start date (12 Nov 2026), that the response includes order and terms links, and that a savings-based payment option exists. It does not state whether prices are static or fetched live, nor any staleness caveats beyond the validity date, which is the main remaining gap.

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?

Two sentences, front-loaded with the trigger condition and the key qualifier (US$, valid from a date). The long parenthetical list of eight priced items is dense but each entry maps to a distinct offering the caller might ask about. Slightly run-on, but no sentence is wasted.

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?

This is a simple zero-argument lookup and an output schema already exists, so the description need not explain return values. It supplies the trigger, currency, validity window, coverage list, and a recommendation for the common fast path — everything an agent needs to call it correctly.

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?

The tool takes zero parameters, so there is no parameter semantics to explain; baseline 4 applies. The description correctly avoids inventing inputs and instead spends its words on scope and content.

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 concrete resource and verb: it returns published Trust Engine AI prices in US$ with order and terms links. The parenthetical enumerates exactly what is priced (free pilot, 7-day test, diet audit, re-test, 24/7 watch, Bulgarian review, pay-from-savings, add-ons), which makes the tool's scope unmistakable. It does not name a sibling to contrast against, which keeps it just below a 5.

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?

Opens with an explicit trigger — 'Use when asked what Trust Engine AI costs' — so the agent knows precisely when to select it. It adds a routing hint for the narrow case ('For a fast fixed-price answer: the 7-day test'). It does not explicitly say when to prefer a sibling such as estimate_switch_savings over this, so no exclusion guidance is present.

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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