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trustmrr_startup

Fetch a verified TrustMRR startup profile by slug to see revenue, MRR, growth, asking price, marketplace status, tech stack, marketing channels, and AI summary.

Instructions

Get TrustMRR startup detail. Returns the full verified profile for a single TrustMRR startup by slug: revenue and MRR, growth, asking price and marketplace status, tech stack, marketing channels, and TrustMRR's AI-generated business summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesTrustMRR startup slug

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations provided, so the description carries the full burden. It lists return fields but does not disclose side effects, authentication needs, rate limits, or idempotency. For a read operation, this is adequate but not thorough.

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 focused sentences deliver the core purpose and content without fluff. The key verb 'Get' and resource 'TrustMRR startup detail' are front-loaded.

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

Completeness4/5

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

For a simple tool with one parameter and no output schema, the description adequately covers what is returned. It lists key data fields, making it useful for an agent to decide if this tool meets the need.

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?

Schema covers 100% of parameters, so baseline is 3. The description adds minimal value beyond confirming the slug identifies the startup. No example or format details are given.

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 clearly states it retrieves a single TrustMRR startup's full verified profile by slug, listing specific fields (e.g., revenue, MRR, growth, tech stack). This distinguishes it from multi-startup tools like trustmrr_startups, but it does not explicitly contrast with siblings.

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?

Usage is implied: to get details for a specific startup when you know its slug. However, no guidance is given on when to use this versus alternatives (e.g., trustmrr_startups for lists, datasets_trustmrr_item for different data). The agent must infer from context.

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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