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

The description adds behavioral context beyond annotations by stating 'Public Store API only, no LLM' and disclosing the cost and payment method ('$0.05/call, x402 (USDC on base)'). These are useful details not present in the annotations, which only provide generic hints.

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 purpose followed by key constraints. Every word earns its place; there is no verbose filler or redundancy.

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 clarify what the 'snapshot' looks like in terms of structure or content. The tool has 8 parameters with rich schema descriptions, but the overall behavior and result format remain somewhat vague, making it less complete for an agent needing to understand the full context.

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 input schema has 100% coverage with descriptions for every parameter, so the baseline is 3. The description does not add parameter-specific details beyond what the schema already provides, nor does it clarify any parameters that the schema leaves ambiguous.

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 uses a specific verb 'Produce' and clearly identifies the resource: 'a current demand-direction snapshot for one declared niche'. It also differentiates from sibling tools by specifying the method ('using observed public Apify Store user metrics') and constraints ('Public Store API only, no LLM').

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 clearly implies when to use this tool: when a demand-direction snapshot for a single niche is needed. It provides context about the data source and cost but does not explicitly mention alternatives or exclusions relative to sibling tools, though the purpose is distinct enough.

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