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

Annotations already declare read-only, non-destructive and open-world, so safety is covered. The description adds genuinely new behavioral context the annotations cannot convey: results are aggregate only, contain no company names or individual records, and include size bands plus best-fit per sector. It stops short of covering pagination or ordering of the sector rows.

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?

Two sentences, front-loaded with the usage trigger followed by the return shape, with no filler. The middle clause listing 'shape of the market, how many companies are qualified, or which sectors and geographies' is slightly enumerative but each example maps to a real use case.

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 needn't be explained, yet the description still summarizes that output as aggregates rather than records — the most decision-relevant fact. Combined with clear usage routing and zero required parameters, an agent has what it needs; only pagination/limit behavior is left implicit.

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 each parameter (focus, limit, sector, geography) is already documented in the schema, and the description adds no syntax, format, or defaulting detail beyond it. Baseline 3 applies; it does implicitly confirm sector and geography are the axes being aggregated, but that is marginal.

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 ('see what is available') plus resource ('Cape Partners' broader scored deal universe') and pins the output shape: aggregate counts by sector with size bands and best fit. It explicitly contrasts with mandate-specific searching, so an agent can distinguish it from find_matches without opening either schema.

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?

Gives a clear condition for use ('when the user wants to see what is available rather than search for one specific mandate') and an explicit exclusion with the alternative ('Prefer a mandate-specific search when the user has one in mind'). No inference required.

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