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datasets_pitchbook_limited_partners_facets

Returns term aggregation counts for PitchBook limited partners, letting you facet by institution type, HQ country/state, or run ID.

Instructions

Facet PitchBook limited partners dataset. Returns terms aggregation counts for the PitchBook limited partners dataset. Facet enum: institution_type, hq_country, hq_state, run_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over name and description, max 256 characters
facetYesFacet enum: institution_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
institution_typeNoExact institution 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: +[
+  "institution_type",
+  "hq_country",
+  "hq_state",
+  "run_id"
+]
  2. Added

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the tool returns aggregation counts (a behavioral trait) but does not mention any additional behaviors like limits, pagination, or whether filters can be combined. It is not misleading, but it adds only the basic return-type information beyond the schema.

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 two sentences, front-loaded with the purpose and the facet enum. Every sentence earns its place; there is no fluff or redundancy. It is concise and immediately informative.

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?

The tool is a simple facet aggregator. The description explains the purpose and the facet enum, and the schema covers the other parameters. The lack of an output schema is partially compensated by the statement that it returns terms aggregation counts. It could mention that other parameters act as filters, but this is implied by the schema. Overall, it is complete for the tool's function.

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 parameters. The description does not add any meaning about parameters beyond what is in the schema; it only repeats the facet enum. With full schema coverage, the baseline of 3 is appropriate.

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 clearly states the tool's purpose: to facet the PitchBook limited partners dataset and return terms aggregation counts. It explicitly lists the facet enum values, and the name plus the phrase 'Returns terms aggregation counts' distinguishes it from sibling tools like search and item. This is a specific verb+resource with clear differentiation.

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 this tool is for getting facet counts, but it does not explicitly state when to use it versus the sibling search or item tools. There is no 'use this when' or 'instead of' guidance. The implied usage is clear from the description, but it leaves the agent to infer the decision context.

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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