Crawlora MCP

datasets_creators_facets

Read-only

Return up to 50 facet buckets with counts for one creators field using the filters from datasets_creators_search. facet accepts niche, country, or verified; page and page_size do not change counts; sort is validated but does not change bucket order. has_email remains a presence filter and no email values are returned; inactive records stay hidden unless include_inactive=true. Use datasets_creators_search to find creator records.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "facet": "<facet>"
    },
    "name": "datasets_creators_facets"
  }
}

Input Schema

Name	Required	Description
`q`	No	Optional full-text query over creator handle, nickname and bio, max 256 characters.
`page`	No	Result page number, 1-based.
`sort`	No	Optional sort order.
`facet`	Yes	required,Required facet. Allowed values: niche, country, verified.
`niche`	No	Optional exact content-niche filter.
`handle`	No	Optional exact handle lookup.
`country`	No	Optional exact creator country/region filter.
`verified`	No	Optional verified-badge filter.
`has_email`	No	Optional contact-email presence filter; no email values are returned.
`page_size`	No	Page size, default 20 and max 100.
`min_followers`	No	Optional minimum follower count.
`include_inactive`	No	Optional. Include deleted/private accounts for historical lookups.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 2, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the readOnly/openWorld annotations, it discloses the 50-bucket cap, pagination and sort irrelevance for count buckets, the presence-only handling of has_email, and that inactive records are hidden unless include_inactive=true. These are meaningful behavioral details an agent would not know from annotations alone.

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 front-loaded with the core purpose and then adds only operationally relevant caveats. Each sentence carries information about what is returned, how facet/pagination/sort behave, and which sibling to use for records.

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?

Given the existing output schema and readOnly annotations, the description provides the remaining context needed: output limit, valid facet values, non-effect of pagination and sort on counts, privacy behavior, inactive-record default, and the search alternative. No important invocation context is missing.

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 most parameter meaning is already documented. The description still adds valuable semantics for page, page_size, sort, has_email, and include_inactive by clarifying which parameters do or do not affect aggregation results.

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 opens with a specific verb and resource: return facet buckets with counts for one creators field. It also distinguishes this aggregation tool from the sibling search tool by naming datasets_creators_search as the way to find creator records.

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 explicitly routes record lookup to datasets_creators_search while framing this tool as the facet-count endpoint, and it names the valid facet values. It also states important constraints: page and page_size do not change counts, and sort does not change bucket order.

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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