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TunnelMind Data API

by ai.tunnelmind
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list_domains

Returns a paginated list of domains from the tracker database. Results are ordered alphabetically by domain name and support cursor-based pagination for full traversal. Filtering by category and minimum score allows targeted data extraction.

Use this tool when:

  • You want to enumerate all known ad-tech or analytics domains above a risk threshold.

  • You need a dataset of tracker domains for offline analysis.

  • You are paginating through a category to build a block list.

Do NOT use this tool when:

  • You need data for a specific domain — use get_domain instead.

  • You are searching by keyword — use search instead.

  • You want domains belonging to a specific company — use get_entity instead.

Inputs:

  • category (query, optional): Filter by surveillance category. One of: ad_tech, analytics, social, fingerprinting, content, cdn, other.

  • min_score (query, optional): Integer 0-100. Exclude domains scoring below this value.

  • limit (query, optional): Number of results per page. Max 100 (paid), 20 (free). Default 50.

  • cursor (query, optional): Pagination cursor from the previous response's next_cursor field.

Returns:

  • Array of domain list items (domain, category, score, prevalence, entity summary).

  • meta.has_more: true if more pages exist.

  • meta.next_cursor: pass as cursor to get the next page.

  • meta.count: number of results in this page.

Cost:

  • Free tier: up to 20 results/page. Anonymous (no key): 10/min, 100/day. Free key: 50/day. Pro/enterprise: up to 100 results/page, included in plan.

Latency:

  • Typical: <200ms, p99: <500ms.

Input Schema

NameRequiredDescriptionDefault
limitNo
cursorNo
categoryNo
min_scoreNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so: alphabetical ordering, cursor-based pagination semantics, tier-dependent result caps, rate limits (10/min, 100/day anonymous; 50/day free key), and latency expectations. These are exactly the constraints an agent must know before calling.

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?

Well front-loaded: purpose first, then usage, inputs, returns, cost, latency. It is longer than strictly necessary for a list endpoint, with several enumerated bullets that restate schema details, but every block is labeled and scannable rather than rambling.

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?

No output schema exists, so the description compensates with a 'Returns' section covering item fields and the `meta.has_more` / `meta.next_cursor` / `meta.count` envelope, which is what an agent needs to actually paginate. Filtering, cost, latency, and pagination are all covered.

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 compensate, and it does for all four parameters: the full enum list for `category`, the semantics of `min_score` ('exclude domains scoring below this value'), the tier-dependent max for `limit`, and the origin of `cursor` ('from the previous response's next_cursor field').

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 first sentence names a specific verb and resource ('Returns a paginated list of domains from the tracker database') and immediately constrains the source (tracker database), ordering, and pagination model. The description explicitly differentiates against named siblings `get_domain`, `search`, and `get_entity`, so an agent can route correctly without opening any schema.

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?

Contains explicit 'Use this tool when' and 'Do NOT use this tool when' blocks, each naming the alternative tool (`get_domain`, `search`, `get_entity`) and the condition that selects it. This is about as unambiguous as usage guidance gets.

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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