datasets_pitchbook_companies_search

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the data is crawled from PitchBook's public sitemap, which hints at potential staleness or coverage limitations, but it does not explain pagination, result limits, or how filters combine. Critical behavioral details like the 10,000-result ceiling appear only in the schema, not in the description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively short, but the first sentence 'Search PitchBook companies dataset' is largely redundant with the tool name. Useful information about crawling and sitemap discovery appears later, and the sort enum list repeats schema content. It is structured reasonably but not tightly front-loaded.

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

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

Given 14 parameters, no output schema, and no annotations, the description only provides data provenance and a sort list. It does not explain return value structure, how filters interact, or when to use which parameters. Though the schema covers parameter documentation, the overall context for an agent selecting this tool is incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the baseline is 3. The description repeats the sort enum but adds no additional semantic meaning beyond what the schema already provides. No extra parameter context is given, making this a neutral contribution.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool enables searching the PitchBook companies dataset, and the second sentence specifies that it searches a crawled public company profile catalog. This distinguishes it from sibling tools like datasets_pitchbook_companies_item or facets, which serve different purposes. The scope is explicit and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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

The description provides no explicit guidance on when to use this tool versus alternatives such as datasets_pitchbook_companies_facets, datasets_pitchbook_companies_item, or pitchbook_company. It implies usage through the word 'search' but lacks exclusions or alternative recommendations. An agent navigating the large sibling list would not know which tool to choose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.