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datasets_pitchbook_companies_facets

Retrieve aggregation counts for PitchBook companies faceted by status, industry, financing, ownership, location, or run ID, with filters to narrow the dataset.

Instructions

Facet PitchBook companies dataset. Returns terms aggregation counts for the PitchBook companies dataset. Facet enum: status, primary_industry, financing_status, ownership_status, hq_country, hq_state, run_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over name and description, max 256 characters
facetYesFacet enum: status, primary_industry, financing_status, ownership_status, hq_country, hq_state, run_id
run_idNoExact crawl run-id filter, max 128 characters
statusNoExact status filter, max 128 characters
hq_stateNoExact headquarters state/region filter, max 128 characters
hq_countryNoExact headquarters country filter, max 128 characters
financing_statusNoExact financing status filter, max 128 characters
max_year_foundedNoMaximum founding year
min_year_foundedNoMinimum founding year
ownership_statusNoExact ownership status filter, max 128 characters
primary_industryNoExact primary industry filter, max 128 characters
min_investor_countNoMinimum number of investors
Behavior2/5

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

No annotations are provided, so the description carries the burden. It discloses the operation (returns counts) and lists valid facets, but does not explain how filters (e.g., q, status) affect the counts, whether counts are for the full dataset or filtered results, or any pagination/limits. This lacks essential behavioral context.

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 extremely concise with two sentences, front-loaded with the primary purpose and the facet enum. Every sentence earns its place with no redundancy.

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

Completeness2/5

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

The tool has 12 parameters and no output schema, yet the description does not explain the returned data structure or how filters interact with facet counts. It is not complete enough for an agent to fully anticipate tool behavior.

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 coverage is 100%, so the baseline is 3. The description repeats the facet enum already present in the schema and adds no additional meaning about parameter semantics or format.

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 identifies the operation ('Facet') and resource ('PitchBook companies dataset'), and explicitly states it returns 'terms aggregation counts.' This distinguishes it from sibling tools like datasets_pitchbook_companies_search and datasets_pitchbook_companies_item.

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 the tool is for obtaining facet counts but does not explicitly state when to use it over search or item tools, nor any exclusions. The phrase 'Returns terms aggregation counts' implies usage for aggregation, but no direct alternatives are named.

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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