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datasets_pitchbook_advisors_facets

Generate facet counts for PitchBook advisors. Filter by service type, HQ country, HQ state, or crawl run ID to analyze advisor distribution.

Instructions

Facet PitchBook advisors dataset. Returns terms aggregation counts for the PitchBook advisors dataset. Facet enum: service_type, hq_country, hq_state, run_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over name and description, max 256 characters
facetYesFacet enum: service_type, hq_country, hq_state, run_id
run_idNoExact crawl run-id filter, max 128 characters
hq_stateNoExact headquarters state/region filter, max 128 characters
hq_countryNoExact headquarters country filter, max 128 characters
service_typeNoExact service provider type filter, max 128 characters
max_year_foundedNoMaximum founding year
min_year_foundedNoMinimum founding year

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / facet / enum
      Added value: +[
+  "service_type",
+  "hq_country",
+  "hq_state",
+  "run_id"
+]
  2. Added

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description bears the full burden. It does disclose the core behavior (returns terms aggregation counts) and lists the facet fields, but omits details on result format, pagination, read-only nature, or how filters interact with the aggregation. Partial disclosure with notable gaps.

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?

Three short sentences with the action and resource front-loaded and the enum list at the end. There is slight redundancy between the first two sentences, both mentioning 'PitchBook advisors dataset', but overall it is compact and easily scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity facet tool with fully described parameters, the description covers the basic return type (aggregation counts) and available facets. However, it lacks explicit usage context versus the search tool, output structure detail, and any behavioral caveats. Adequate but incomplete.

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%, and every parameter already has a clear description. The tool description adds no parameter semantics beyond restating the facet enum, which is already in 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?

The description states a specific verb ('Facet', 'Returns terms aggregation counts') and a specific resource ('PitchBook advisors dataset'), and enumerates the valid facets. This clearly identifies it as the aggregation/faceting tool for that dataset and distinguishes it from sibling search/item tools.

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: the agent can infer to use this when it needs facet aggregation counts. However, there is no explicit guidance about when to prefer this over datasets_pitchbook_advisors_search or other sibling facet tools, no exclusions, and no alternative conditions.

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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