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TunnelMind Data API

by ai.tunnelmind
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search

Searches both the domains table and the entities table simultaneously. Returns matching domains (by domain name) and entities (by name or slug) in a single response. Minimum 2 characters, maximum 100 characters.

Use this tool when:

  • You have a partial name and need to identify what tracker or entity it belongs to.

  • You want to find all TunnelMind records related to a company name like "Google" or "Oracle".

  • You are resolving an ambiguous domain (e.g., does criteo.com appear in the tracker DB?).

Do NOT use this tool when:

  • You know the exact domain — use get_domain instead (faster, more complete).

  • You know the exact entity slug — use get_entity instead.

  • You want to browse by category or industry — use list_domains or list_entities.

Inputs:

  • q (query, required): Search string, 2-100 characters. Matched against domain names and entity names/slugs.

Returns:

  • domains: array of matching domain records (list item format).

  • entities: array of matching entity records (list item format).

  • Both arrays may be empty if no matches found. No pagination — results are capped at 20 per type.

Cost:

  • Anonymous (no key): 10/min, 100/day. Free key: 50/day. Pro/enterprise: included in plan.

Latency:

  • Typical: <200ms, p99: <500ms.

Input Schema

NameRequiredDescriptionDefault
qYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so well: it discloses the returned arrays, empty-result behavior, a 20-per-type cap, no pagination, rate limits by auth tier, and latency expectations. These are meaningful operational traits 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?

The description is structured and front-loaded: purpose first, then when/when-not guidance, then inputs, returns, cost, and latency. Although it is longer than a minimal sentence, each section earns its place by answering an invocation question.

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?

There is no output schema, but the description explains the return shape, empty-array behavior, and result cap. Together with the alternatives, rate limits, and latency, it gives an agent everything needed to call this search tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must explain the single parameter. It does: q is required, must be 2-100 characters, and is matched against domain names and entity names/slugs, adding search semantics beyond the schema's type and length constraints.

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 and resource: search across both the domains table and entities table, returning matches by domain name or entity name/slug. It clearly distinguishes the tool from exact-lookup siblings like get_domain and get_entity.

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?

It gives explicit when-to-use cases and explicit do-not-use cases, naming the better alternative in each exclusion: get_domain, get_entity, list_domains, and list_entities. This leaves little ambiguity for an agent choosing among siblings.

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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