datasets_pitchbook_limited_partners_search

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

With no annotations provided, the description carries the full burden. It discloses that data comes from a crawl of PitchBook's public sitemap and preemptively explains that missing FAQ sections are normal. This adds useful behavioral context beyond the raw schema, though it does not cover all possible traits (e.g., pagination limits, data completeness).

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 about 60 words and front-loads the primary purpose with the first sentence. Some redundancy exists (e.g., 'Discovered from PitchBook's public sitemap' restates 'crawled public', and the sort enum duplicates schema info), but it remains concise and logically structured.

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?

For a search tool with 10 optional parameters and no output schema, the description provides dataset context and a data-quality caveat. However, it lacks an explicit note about typical return format or result pagination (beyond what the schema states) and gives no examples. It is adequate but leaves the agent to infer several operational details.

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 covers 100% of parameters with descriptions, so the baseline is 3. The description only repeats the sort enum values already present in the schema and does not add new meaning to fields like `q`, `hq_country`, or `institution_type`. It adds no value beyond what the schema already provides.

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 opens with 'Search PitchBook limited partners dataset' and then specifies it 'Searches the crawled public PitchBook limited partner (institutional investor — e.g. pension fund, endowment, insurance company) profile catalog stored in a search index.' This gives a specific verb (search) and resource (PitchBook LP catalog), clearly distinguishing it from sibling item/facets tools.

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 implies the tool is for searching the public LP catalog and provides context about the data source, but it never explicitly states when to use this tool versus alternatives like datasets_pitchbook_limited_partners_item or facets. There are no clear 'when not to use' statements or references to sibling tools.

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