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datasets_pitchbook_companies_search

Search public PitchBook company profiles by name, industry, headquarters, status, founding year, and investor count; filter and sort results to find target companies.

Instructions

Search PitchBook companies dataset. Searches the crawled public PitchBook company profile catalog stored in a search index. Discovered from PitchBook's public sitemap. Sort enum: relevance, name_asc, year_founded_desc, investor_count_desc, recently_crawled_desc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over name and description, max 256 characters
pageNoPage number, defaults to 1
sortNoSort enum: relevance, name_asc, year_founded_desc, investor_count_desc, recently_crawled_desc
run_idNoExact crawl run-id filter, max 128 characters
statusNoExact status filter (e.g. Private, Public, Acquired, Out of Business), max 128 characters
hq_stateNoExact headquarters state/region filter, max 128 characters
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "relevance",
+  "name_asc",
+  "year_founded_desc",
+  "investor_count_desc",
+  "recently_crawled_desc"
+]
  2. Added

TDQS

C2.8/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of disclosing behavioral traits. It does add useful provenance information ('crawled public PitchBook company profile catalog', 'Discovered from PitchBook's public sitemap'), but it does not describe the response shape, default sort behavior, pagination semantics beyond the schema, or whether an empty query returns all records. This leaves significant behavioral gaps.

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?

The description is short, but not every sentence earns its place: the first sentence largely restates the tool name, and the sort enum list duplicates schema content. The middle sentence about the crawled catalog and public sitemap is the only genuinely additive part. It is concise but contains 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?

With 14 parameters, no annotations, and no output schema, the description should provide more operational context. It explains where the data comes from but not what results look like, how to construct an effective search, or how pagination and filtering interact. An agent would struggle to know what to expect or how to choose parameters beyond reading the schema.

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 parameters are already well documented in the schema. The description adds only a redundant restatement of the sort enum, which provides no new meaning beyond the schema. This matches the baseline of 3.

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 clearly identifies a specific verb and resource: searching the PitchBook companies dataset stored in a search index. It also clarifies that this is a search over crawled public company profiles. However, it does not explicitly differentiate itself from sibling tools like datasets_pitchbook_companies_facets or datasets_pitchbook_companies_item, so it falls short of 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 Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives such as the facets or item lookup tools. It does not state what kind of queries are appropriate, whether filters should be used together, or when a different PitchBook dataset tool would be better. The usage context is left entirely to inference.

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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