ICP Qualification

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

Annotations mark the tool as readOnlyHint=true and idempotentHint=true, and the description confirms it is a scoring operation returning JSON, with no destructive actions. It adds context about the model structure and scaling constraints, and mentions the API key requirement for company_id, providing behavioral clarity beyond annotations.

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 with a clear first sentence stating the purpose, then breaking down the model and input options. It is reasonably concise, though the list of company_data keys could be shortened or referenced from an external source.

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 (3 parameters, output schema exists), the description covers inputs, model components, and return values adequately. It mentions constraint context and recommended action, but does not elaborate on error handling or detailed output schema (though the schema is separately defined). Overall, it provides sufficient context for an AI agent.

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?

With 0% schema description coverage, the description compensates well by detailing company_data with example keys and explaining company_id and scoring_config. However, scoring_config is described only as 'override default scoring parameters' without listing possible keys or formats, leaving some ambiguity.

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 that the tool scores a prospect against the Artefact 14.5-point ICP model, specifying the three fit components (Firmographic, Behavioral, Strategic) and the return values. It distinguishes itself from sibling tools like run_rfm and score_pipeline_health by focusing on ICP qualification.

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 clear instructions on input options: use company_id (with HubSpot API key) or company_data (JSON string) and optional scoring_config. It lists example keys for company_data. However, it does not explicitly state when to use this tool over alternatives or when not to use it.

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