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

The description adds valuable behavioral context beyond annotations: it discloses the cost ('$0.05/call, x402 (USDC on base)') and notes that it uses only the Public Store API with no LLM, implying deterministic evidence-based behavior. Annotations already indicate non-read-only and non-idempotent behavior, which is not contradicted. It does not detail all side effects, but the added cost/source context is useful.

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 that states the core purpose and then adds crucial operational constraints (API-only, no LLM, cost). It contains no filler and is highly readable for an agent.

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?

There is no output schema, and the description does not explain the return value or report format beyond the assessment concept. Some clues exist in parameter descriptions (e.g., detailLevel mentions 'output in the dataset row'), but the description itself is thin on output details. Given the moderate complexity, it is adequate but could be more complete.

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 description coverage is 100%, so parameters are well documented in the schema. The description does not add parameter-specific details beyond repeating the idea assessment concept. It mentions cost but not per-parameter semantics. Baseline of 3 is appropriate since the schema carries the parameter documentation.

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 action ('Assess one proposed Apify Actor idea') and the resource/scope ('against public Store similarity, activity, quality, competition and visible pricing evidence'). It distinguishes the tool from siblings by emphasizing single-idea validation, which contrasts with market-gap-finder or niche-demand-radar.

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 usage is implied through the purpose: this is for validating an individual idea. However, there is no explicit 'when to use' or 'when not to use' guidance, and no alternatives are mentioned. The phrase 'Public Store API only, no LLM' hints at constraints but does not specify how it should be selected relative to sibling tools.

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