search_suppliers

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

With no annotations provided, the description carries the full transparency burden, and it does so well. It reveals the conditional behavior depending on whether a supplier data API is configured, the fallback output (real public markets, manufacturing clusters, B2B directories, verification checklist), and explicitly states that supplier names, prices, and MOQs are never invented. This is valuable behavioral context beyond any structured fields.

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 concise and front-loaded with the core purpose and scope. The second sentence adds necessary behavioral detail about fallback behavior and anti-hallucination guarantees without being verbose. 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?

The description covers the tool's purpose, geographic scope, conditional behavior, and data-integrity policy, which is strong for a research/search tool. An output schema exists, so return structure is covered. The main missing piece is explicit guidance on when to prefer this tool over sibling research/search tools, but overall the description is sufficiently complete for a competent agent.

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 schema has 0% description coverage, and the description does not directly explain each parameter. However, the parameter names are self-explanatory, and the description adds meaningful context for 'location' by naming Parrys, Chennai, Tamil Nadu, and nationwide. It does not elaborate on 'supplier_type', but the default of 'any' and the tool's purpose make this gap understandable.

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 ('Research sourcing') and a specific resource ('suppliers for a product in India'), with geographic scope (Parrys, Chennai, Tamil Nadu or nationwide). This is distinct from the sibling research/analysis tools, which focus on demand, competition, profitability, or listings rather than supplier sourcing.

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 intended use case is clear: use this tool when researching sourcing and suppliers for a product in India. It does not explicitly name alternatives or state when not to use it, but the context alone is enough for an agent to distinguish it from the product-research and competition-analysis siblings.

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