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datasets_facebook_pages_search

Search the Facebook Pages dataset. Searches public Facebook Page contact records stored in a search index — website, email, phone, WhatsApp, category and like count, discovered through business-search enumeration, domain-scoped scans, and…

Instructions

Search the Facebook Pages dataset. Searches public Facebook Page contact records stored in a search index — website, email, phone, WhatsApp, category and like count, discovered through business-search enumeration, domain-scoped scans, and Wikidata seeding, then hydrated from each Page's public About tab. Sort enum: relevance, likes_desc, likes_asc, hydrated_at_desc, hydrated_at_asc. Billing: this search costs 1 credit per record returned, with a minimum of 2 (an empty result costs 2, a full page of 100 costs 100).

Input Schema

NameRequiredDescriptionDefault
qNoFull-text query over title and address, max 256 characters
pageNoPage number, defaults to 1
sortNoSort enum: relevance, likes_desc, likes_asc, hydrated_at_desc, hydrated_at_asc
page_idNoExact Facebook Page id filter, max 128 characters
categoryNoExact Page category filter (case-insensitive), max 128 characters
has_emailNoFilter by a public contact email
has_phoneNoFilter by at least one public phone number
max_likesNoMaximum Page like count
min_likesNoMinimum Page like count
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
identifierNoExact Page username/identifier filter (case-insensitive), max 128 characters
has_websiteNoFilter by a linked website
has_whatsappNoFilter by a public WhatsApp contact
hydrated_afterNoRecords last refreshed on or after this date (RFC3339 or YYYY-MM-DD)
hydrated_beforeNoRecords last refreshed on or before this date (RFC3339 or YYYY-MM-DD)
discovery_sourceNoExact filter for how the Page was discovered (e.g. business_search, warc_domain_scan, wikidata), max 128 characters

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort / enum
      Added value: +[
      +  "relevance",
      +  "likes_desc",
      +  "likes_asc",
      +  "hydrated_at_desc",
      +  "hydrated_at_asc"
      +]
  2. Addedv1.16.0

TDQS

B3.4/5.0
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 it does disclose a genuinely important trait: credit-based billing of 1 credit per returned record with a 2-credit floor (empty result costs 2, 100 records costs 100). It also explains data provenance and hydration (business-search enumeration, domain scans, Wikidata seeding, About-tab hydration). It omits auth requirements, rate limits, and the shape of returned records (no output schema exists), so it is not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded, which is good, but the middle sentence is an overlong provenance/hydration narrative of limited use for invocation, and the sort enum is duplicated from the schema. The billing sentence is the most valuable and could have come earlier. Roughly a third of the text is restatement.

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 16-parameter, all-optional search with a fully documented schema and no output schema, the description supplies the pieces the schema cannot: cost model and data lineage. The clamping rule (page * page_size <= 10000) and defaults live in the schema, so nothing critical is missing, though return-value shape is unaddressed.

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 every one of the 16 parameters is already documented in the schema; the baseline is 3. The description restates the sort enum verbatim (already in the schema) and adds no syntax or format guidance beyond it. It does not improve on the schema's own parameter documentation.

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 gives a specific verb and resource ("Search the Facebook Pages dataset") and enumerates exactly what the records hold — website, email, phone, WhatsApp, category, like count — which cleanly separates it from datasets_facebook_pages_item and datasets_facebook_pages_facets. It stops short of naming those siblings explicitly, so the differentiation is inferable rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance: nothing tells the agent when to prefer this search over datasets_facebook_pages_facets (aggregation) or datasets_facebook_pages_item (single record). The billing note hints at cost sensitivity but does not route the agent between tools. Usage must be inferred from the tool name alone.

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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