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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations: it scans the entire catalog, serves entity-less cross-cutting queries, and returns brand, title, price/price range, fulfillment, and sourcing scores. It does not disclose ranking logic or pagination defaults, but it provides meaningful additional context.

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 three sentences with no filler: first sentence states scope and main filters, second gives concrete trigger phrases and usage condition, third summarizes the return payload. It is front-loaded and every sentence earns its place.

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 high complexity (30 parameters, no output schema, 23% schema coverage), the description is not complete enough. It provides good high-level orientation and output hints, but many filter semantics and scoring definitions remain unexplained, so an agent cannot reliably choose appropriate values for the full range of parameters without additional inference.

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 only 23%, and the tool has 30 parameters, so the description must compensate. It names only a subset of filters (max/min retail price, category, brand, exclude gated, exclude Amazon private label) and never explains key scoring parameters like margin_signal, composite_score, velocity_score, or gating_risk_score. The generic phrase 'sourcing scores' does not give agents enough meaning to choose among the many filter parameters confidently.

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 opens with a specific verb-resource pair: 'Find top sourcing-pick ASINs across the entire catalog', and it names the key optional filters. It also differentiates from entity-specific siblings by explicitly covering 'any cross-cutting question where they have NOT named a specific entity yet', making the tool's purpose and scope clear.

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 gives explicit trigger phrases ('top sourcing picks', 'best ASINs to source', 'ASINs under $X with rising demand') and a clear use condition: cross-cutting questions with no named entity. It does not name competing sibling tools or say when to prefer alternatives like search_products or find_sourcing_opportunities, so the usage guidance is strong but not fully comprehensive.

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