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

With no annotations provided, the description fully discloses behavioral traits: it is a probabilistic leading-signal estimate, not certainty, not insider information, based on public USAspending.gov and EDGAR data. This helps the agent understand the tool's limitations and data sources.

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 well-structured, starting with the primary output, then data sources, then caveats. It is slightly long but every sentence adds necessary information.

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 no output schema, the description comprehensively lists what is returned (score, reasoning, award-velocity, trajectory, agency mix, etc.). It covers key aspects but could specify output format for better parsing.

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 sole parameter 'name' has a clear schema description with an example. The tool description elaborates on how the name is used, adding context beyond the schema. Since schema coverage is 100% and the parameter is simple, the description adds value.

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 takes a contractor name and returns a detailed signal profile, including acquisition-likelihood score, reasoning, award-velocity, trajectory, and more. It is distinct from sibling tools 'rising_contractors' and 'search_awards', which focus on listing rising contractors and searching awards respectively.

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 indicates when to use: given a federal contractor NAME. It provides context that the data is public and the signal is probabilistic, not investment advice. However, it does not explicitly state when not to use or suggest alternatives.

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