Score ICP Fit

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

Annotations already declare readonly, destructive false, idempotent, and open world. The description adds important behavioral context beyond annotations, including that it requires APIFY_TOKEN, consumes Apify credits per call, and that icp_description requires an llm_api_key. This provides a clearer picture of the tool's operational constraints.

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 extremely concise with two sentences that front-load the core purpose and output. Every sentence provides essential information without fluff, making it easy for an agent to quickly understand the tool.

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 complexity of 9 parameters and no output schema, the description adequately covers key aspects: output format, ICP definition methods, auth requirements, and credit consumption. It does not detail per-signal breakdown structure or behavior when multiple input methods are used, but it is sufficiently complete for typical usage.

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 100% with all parameters described. The description adds value by explaining that parameters like template, scoring_config, and icp_description are alternative ways to define the ICP, and that icp_description requires llm_api_key. This clarifies parameter dependencies and usage patterns beyond the schema alone.

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 scores a company against an ICP with weighted signals and specifies the exact output format including icp_score, icp_tier, and per-signal breakdown. It distinguishes itself from sibling tools like aggregate_gtm_signals by focusing specifically on ICP scoring.

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 explains how to define the ICP using template, scoring_config, or plain-English description, and mentions prerequisites like APIFY_TOKEN and credit consumption. However, it does not explicitly state when not to use this tool or suggest alternatives, so it is slightly lacking in exclusion guidance.

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