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

Annotations already cover readOnly and openWorld, so the bar is lower, and the description adds the crucial non-schema trait: 1 credit per record with a 2-record minimum, plus the warning to keep page_size small. It stops short of describing rate limits, auth requirements, or crawl freshness, keeping it out of 5 territory.

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?

Three sentences, front-loaded with purpose, then the cost caveat, then the routing rule. No filler, and the most decision-relevant constraints come before the alternative-tool guidance.

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?

An output schema exists so return values need no explanation here; all 11 parameters are documented at 100% in the schema; and the description supplies purpose, credit economics, and usage routing. Nothing an agent needs to call it correctly is missing.

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?

Schema coverage is 100% so the baseline is 3, but the description adds real meaning the schema lacks: the cost implication of page_size and the practical reason to tune it. The remaining 10 params get no description-level commentary, so it does not fully compensate upward.

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?

States a specific verb (Search) and resource (PitchBook investor and fund-manager profile catalog) and even names what the records contain (overview and investment previews). This clearly distinguishes it from sibling datasets_pitchbook_companies_search and datasets_pitchbook_funds_search without opening their schemas.

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?

"Use this when researching investors rather than operating companies" gives a clear when-to-use condition plus the alternative category. It never names the actual sibling tool (e.g. datasets_pitchbook_companies_search), so routing is slightly inferential, but the guidance is real.

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