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 adds helpful context by mentioning the cost ($0.25) and the research-signal disclaimer, and explains the effect of min_coverage and weights. However, it does not disclose data freshness, rate limits, or any other limitations beyond the disclaimer, so transparency is partial but not comprehensive.

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 concise and front-loaded: the first sentence states the core function, the second clarifies two important parameters, and the third provides cost and risk disclaimers. Every sentence serves a purpose with no fluff or redundancy. It is appropriately sized for the tool's complexity.

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?

The description provides a clear purpose, explains some parameters, and includes cost and disclaimers. Return values are covered by the output schema, so that is not needed. However, it lacks usage guidelines and does not clarify how this tool differs from sibling tools like screen_companies or standard_score. This leaves an agent uncertain about when to select this tool.

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 0%, so the description must compensate. It provides meaningful explanations for min_coverage ('filters thinly scored names') and weights ('re-weights the factors'). However, limit and min_composite are not explained, leaving a gap. The partial coverage of two out of four parameters makes this a 3.

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's purpose: ranking companies by a composite factor score across five evidence sources. It uses a specific verb 'Rank' and identifies the resource, but it does not explicitly differentiate from sibling tools like screen_companies or standard_score, so it lacks explicit sibling differentiation.

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 guidance on when to use this tool versus alternatives. It does not mention any prerequisites, use cases, or exclusions. The disclaimer 'RESEARCH SIGNAL, NOT INVESTMENT ADVICE' is a risk notice, not usage guidance. Without alternatives or context, the agent is left to guess when this tool is appropriate.

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