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 of behavioral disclosure and does so comprehensively. It explains the methodology (patent-pending SMI, weather-normalized electricity demand analysis across 8 regions), output format (regional/national scores, trend direction, comparison to INDPRO data), scale interpretation (INVERTED scale with specific ranges and meanings), and typical users. This provides rich behavioral context beyond basic functionality.

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 with the core functionality in the first sentence. Each subsequent sentence adds valuable information: methodology, geographic scope, output details, scale interpretation, and use cases. While slightly dense, every sentence earns its place by providing essential context for this specialized tool.

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 tool's complexity (specialized economic indicator with inverted scoring) and lack of both annotations and output schema, the description provides complete context. It explains what the tool does, how it works, what it returns (scores, trends, comparisons), how to interpret results (inverted scale with ranges), and who uses it. This fully compensates for the missing structured metadata.

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 description coverage, so the baseline would be 3. However, the description explicitly states there are no parameters needed ('Detect US manufacturing output changes...' implies a parameterless query), which adds value beyond the empty schema by confirming this is a straightforward data retrieval tool without filtering options. This justifies a score above baseline.

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: detecting US manufacturing output changes using the Supply Manufacturing Index (SMI) that analyzes electricity demand across 8 US power grid regions. It specifies the methodology (weather-normalized electricity demand analysis), distinguishes from official government reports by being a leading indicator, and differentiates from siblings like 'get_economic_indicators' by focusing specifically on manufacturing output.

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 detecting manufacturing output changes up to 24 hours before official reports, specifically mentioning use cases by commodity traders, economic analysts, and hedge funds. However, it doesn't explicitly state when NOT to use it or name specific alternative tools among the siblings, though the specialized focus implies it's for manufacturing-specific analysis rather than general economic indicators.

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