SupplyMaven API Pro

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

No annotations are provided, so the description carries the full burden. It discloses behavioral traits by specifying the return data types (e.g., prices, storage levels, utilization rates) and the tool's role in providing a 'disaggregated view' for cost analysis. However, it doesn't mention potential limitations like data freshness, rate limits, or error handling, leaving some behavioral aspects unclear.

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 then elaborating on returns and usage. Every sentence adds value, such as specifying the user groups and differentiating from aggregated views. It could be slightly more concise by combining some details, but overall it's well-structured without wasted words.

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 (detailed energy market data) and lack of annotations and output schema, the description is largely complete. It explains the tool's purpose, usage, and output semantics thoroughly. However, it doesn't cover potential behavioral aspects like data sources or update frequency, which could enhance completeness for such a data-rich tool.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by explaining the tool's output semantics, detailing what data is returned (e.g., crude oil prices, natural gas storage), which compensates for the lack of an output schema. This goes beyond the schema's scope, earning a high score.

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 explicitly states the verb 'Get' and specifies the resource as 'comprehensive US energy market status for supply chain cost analysis,' with detailed components like crude oil prices, natural gas spot prices, etc. It clearly distinguishes from siblings by mentioning it's the 'disaggregated view behind the GDI Energy pillar,' contrasting with tools like 'get_energy_forecast' or 'risk_pillar_breakdown' that likely provide aggregated or different data.

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 explicit usage context: 'Used by supply chain cost analysts, transportation managers, and energy procurement teams.' It also distinguishes when to use this tool by stating it's for a 'full picture of energy costs' instead of a 'single risk number,' implying alternatives like 'risk_pillar_breakdown' or 'supply_chain_risk_assessment' might offer summarized views, though it doesn't name specific siblings.

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