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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

datasets_x_users_facets

Returns value counts for X users grouped by a chosen facet such as verification, bio presence, external URL, or source tier, applying your search filters.

Instructions

Facet the X users dataset. Returns value counts for the X users dataset by the required facet: is_blue_verified, has_bio, has_external_url or source_tier. The counts follow the search filters, including q, follower and ratio ranges, and creation or crawl dates. At most 50 values come back, largest count first.

Input Schema

NameRequiredDescriptionDefault
qNoFull-text query over username, name, bio and location, max 256 characters
sortNoSort enum: relevance, followers_desc, followers_asc, crawled_at_desc, crawled_at_asc, created_at_desc, created_at_asc
facetYesFacet enum: is_blue_verified, has_bio, has_external_url, source_tier
has_bioNoFilter by a non-empty profile bio
usernameNoExact username filter (case-insensitive), max 128 characters
max_ratioNoMaximum follower-to-following ratio
min_ratioNoMinimum follower-to-following ratio
source_tierNoExact filter for which seed tier discovered this account
crawled_afterNoRecords last refreshed on or after this date (RFC3339 or YYYY-MM-DD)
created_afterNoAccounts created on or after this date (RFC3339 or YYYY-MM-DD)
max_followersNoMaximum follower count
min_followersNoMinimum follower count
crawled_beforeNoRecords last refreshed on or before this date (RFC3339 or YYYY-MM-DD)
created_beforeNoAccounts created on or before this date (RFC3339 or YYYY-MM-DD)
has_external_urlNoFilter by a linked external URL
is_blue_verifiedNoFilter by the X blue-check verification flag

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / facet / enum
      Added value: +[
+  "is_blue_verified",
+  "has_bio",
+  "has_external_url",
+  "source_tier"
+]
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "relevance",
+  "followers_desc",
+  "followers_asc",
+  "crawled_at_desc",
+  "crawled_at_asc",
+  "created_at_desc",
+  "created_at_asc"
+]
  2. Addedv1.6.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does useful work: it discloses the 50-value cap, the largest-count-first ordering, and the fact that counts follow the applied filters. It omits auth/rate-limit context, but for a read-only facet endpoint this is solid disclosure.

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?

Three sentences, front-loaded with purpose, then facet values, then behavior. No filler or restated boilerplate; every sentence carries information.

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?

With no output schema, the description adequately explains the return shape (value counts, capped at 50, sorted). Parameter documentation is fully delegated to a complete schema. The only gap is the absence of explicit guidance on when to prefer this tool over its X-users siblings.

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 description coverage is 100%, so the schema already documents all 16 parameters, and the description largely repeats the facet enum it also lists. It adds one genuinely useful note — that q, follower/ratio ranges, and date filters all constrain the returned counts — but otherwise does not go beyond the schema. Baseline 3 applies.

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?

States a specific verb ('Facet') and resource ('X users dataset'), enumerates the valid facet values, and defines the output as value counts. An agent can distinguish this aggregate tool from datasets_x_users_search and datasets_x_users_item without opening the schema.

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?

The description implies usage (get aggregate counts that respect the search filters) but never explicitly states when to choose this over the sibling search/item tools or what conditions make faceting appropriate. Usage is inferable but not routed.

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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