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datasets_journalists_facets

Read-only

Facet aggregation over the journalists dataset (by outlet, vertical, topic, or contact availability). facet=outlet lists every outlet in one response; page/page_size are ignored.

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_journalists_facets"
  }
}

Input Schema

NameRequiredDescriptionDefault
qNoOptional full-text match on the journalist's name, title, and bio, max 256 characters.
pageNoResult page number, 1-based, default 1; page times page_size must not exceed 10000.
sortNoOptional sort order. Allowed values: relevance, name_asc, outlet_asc, crawled_desc, readiness_desc. Defaults to relevance with q, otherwise outlet_asc.
facetYesRequired facet to aggregate. Allowed values: outlet, vertical, topic, contact_type, record_type, role_type, email_kind, outreach_readiness_band.
topicNoOptional exact topic filter, e.g. security, stablecoins. Use the values returned by facets?facet=topic.
outletNoOptional exact outlet filter, e.g. techcrunch, coindesk. Use the outlet ids returned by facets?facet=outlet.
verticalNoOptional exact beat-vertical filter. Allowed values: tech, crypto, marketing, consumer_tech, consumer_policy, cybersecurity, health, gaming, climate, business, entertainment, sports, legal, science, politics, real_estate, automotive, travel, food, education, design, film_tv, fashion, music, personal_finance, tech_independent, culture_independent, local_news, construction, banking, retail, aerospace_defense, energy, agriculture, local_business, general_news.
page_sizeNoPage size, default 20, max 100; page times page_size must not exceed 10000.
role_typeNoOptional role classification filter. Allowed values: staff, editor, reporter, contributor, freelancer, columnist, non_editorial, unknown.
email_kindNoOptional email semantics filter. Allowed values: individual_work, individual_personal_public, shared_desk, tips_or_submissions, outlet_generic, unknown.
record_typeNoOptional record classification filter. Allowed values: person, desk, organization, syndicated_byline, unknown.
contact_typeNoOptional exact contact-availability filter. Allowed values: email, social, none.
min_outreach_readinessNoOptional minimum outreach-readiness score from 0 to 100.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds one genuinely useful behavioral note (facet=outlet returns every outlet in a single response and ignores page/page_size), but says nothing about result size, ordering, or other pagination quirks.

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?

Two tight sentences, zero waste, with the core purpose front-loaded and the behavioral caveat second. Nothing extraneous.

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?

An output schema exists so return values need no explanation, and annotations cover the read-only profile. For a 13-parameter facet tool the description is nearly sufficient, missing only explicit routing guidance against the search/item 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 13 parameters including the full facet enum. The description adds only the pagination-ignored note and names a subset (outlet, vertical, topic, contact availability) of the 8 valid facet values. Baseline 3 is appropriate.

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?

States a specific verb and resource ('Facet aggregation over the journalists dataset') and names the aggregation dimensions, which distinguishes it from datasets_journalists_search and datasets_journalists_item without opening their schemas. It stops short of an explicit sibling comparison, so a 4 rather than a 5.

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?

Usage is implied rather than stated: the schema descriptions point agents to 'the values returned by facets?facet=topic/outlet', which suggests discovery-before-filtering, but the description itself never says when to call this instead of search or item. No exclusions or prerequisites are given.

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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