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

With no annotations provided, the description carries the transparency burden. It discloses that size values are in $Millions, which affects interpretation of min/max parameters, and explains the exclusion semantics of the active_private status. It also reveals that output rows include ticker/cikcode for joins, which is useful behavioral context. However, it does not address pagination, sorting defaults, or output structure in detail, leaving some gaps.

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 exactly two sentences, front-loaded with the action verb and purpose, then a concrete example, then a clarifying detail about status semantics. Every clause earns its place; there is no redundancy or filler.

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 the tool's complexity (23 parameters, no annotations, no output schema), the description is somewhat thin. It covers the primary purpose, a sample query, and the key status behavior, but omits details on output structure, pagination, sorting defaults, and most parameter semantics. For a screening tool with this many options, more behavioral context would help the agent invoke it correctly, though the existing text covers the essential use case adequately.

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 description coverage is 0%, so the description must compensate. It conveys the conceptual filter categories (sector, geography, size in $Millions, founding year) and explains the crucial status meaning, which clarifies several related parameters. It does not map these to specific parameter names or explain many params (e.g., q, sort, limit, fields, has_ticker), but the parameter names in the schema are largely self-explanatory. The description adds moderate value but is not comprehensive for 23 params.

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 a clear action verb 'SCREEN' and identifies the resource as 'private companies', listing specific filter dimensions (sector, geography, financing/business status, size, founding year). It distinguishes from sibling tools by noting it is the 'PRIMARY tool for list questions' and that rows carry ticker/cikcode for joining to public data, which is unique among the private_markets family.

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 explicitly states when to use: 'PRIMARY tool for list questions like...' with a concrete example query. It also clarifies the critical status behavior ('status=active_private excludes public/acquired/defunct'). It stops short of explicitly naming alternative tools for single-entity or deal-specific queries, so it lacks an explicit when-not-to-use, but the primary-tool framing implies appropriate context.

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