score_local_lead

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

With no annotations provided, the description must carry full behavioral disclosure. It states that scoring is based on observable signals and yields a 0–100 score, but it does not explain the scoring model, whether the operation is read-only, or what the response structure contains. This leaves significant ambiguity for an agent.

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 a single, front-loaded sentence with no wasted words. It efficiently communicates the core action, target, and output scale.

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?

Despite having 7 parameters and no output schema, the description fails to specify what the tool returns (e.g., a number or JSON object), how the score is computed, or the role of each input. This is inadequate for a complex scoring tool with no annotations or output schema.

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 only 14% (only 'trade' has a description). The tool description uses the generic phrase 'observable signals' but does not define how individual parameters (e.g., review_count, google_rating, responds_to_reviews) influence the score. The parameter names provide some semantic clues, but the description adds minimal value beyond the schema.

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 a specific verb ('Score'), a resource ('local business lead'), an output range (0–100), and a purpose ('outreach priority'). It distinguishes from sibling tools like generate_cold_email by focusing on scoring rather than generation.

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 implies when to use the tool—when you have a lead to score for outreach—but it does not explicitly mention alternatives or exclusions. No mention of when not to use it or how it relates to sibling tools.

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