SupplyMaven API Pro

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

With no annotations provided, the description carries the full burden and does so well by disclosing key behavioral traits: it monitors specific regions, returns data with a 7-day history, uses weather normalization, and serves as an early indicator. It does not mention rate limits, authentication needs, or data freshness, keeping it from a perfect score.

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 appropriately sized and front-loaded, starting with the core purpose and key details. Every sentence adds value, but it could be slightly more concise by integrating some details (e.g., the list of regions or patent-pending note) more tightly without losing clarity.

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 the tool (monitoring multiple regions with specialized analysis), no annotations, and no output schema, the description is largely complete. It explains the purpose, methodology, output format, and use cases. However, it lacks details on error handling or exact output structure, which could be helpful for an 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 tool has 0 parameters with 100% schema coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics (e.g., SMI score, regional breakdown, anomalies ranked by severity), adding value beyond the empty input schema. A baseline of 4 is given as it compensates well for the lack of parameters.

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's purpose with specific verbs ('detect unusual electricity demand patterns', 'monitors 8 US power grid regions', 'returns current SMI score') and distinguishes it from siblings by focusing on manufacturing anomalies through electricity demand analysis, unlike tools like 'commodity_price_monitor' or 'get_port_congestion_trends'.

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 provides clear context for when to use this tool ('for early manufacturing signals', 'to anticipate supply changes'), mentioning specific user groups (commodity traders, procurement teams). However, it does not explicitly state when not to use it or name alternative tools among siblings for similar purposes.

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