get_surface_analysis

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

Despite no annotations, the description discloses key behaviors: returns distance/bearing to fronts and pressure centers, update frequency (every 3 hours for analysis), CONUS-only coverage, and approximate warm/cold sector detection. It provides adequate transparency, though it could mention any rate limits or authentication needs.

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 well-structured with sections and bullet points. Every sentence adds value, and the most important information (purpose, what it returns) is front-loaded. No trivial or redundant text.

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 (7 optional parameters, output schema, no annotations), the description is exceptionally complete. It covers all parameters, provides usage examples, discloses limitations (CONUS, approximate detection, data source), and includes example queries. It fully compensates for the lack of annotations and schema descriptions.

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?

With 0% schema description coverage, the description fully explains all 7 parameters. It details product (analysis vs forecast, day usage), detail (standard vs full), scope (local vs all with 400km threshold), units (with field overrides), and lat/lon (optional, defaults to primary). This adds significant meaning beyond the schema.

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 retrieves surface analysis or forecast showing fronts, pressure centers, and warm/cold sectors. It provides specific verb-resource pairs like 'Get surface analysis' and 'Returns distance and bearing,' and distinguishes it from sibling tools like get_conditions and get_forecast.

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 includes a 'Use when:' section with example queries, explains when to use 'analysis' vs 'forecast' and 'local' vs 'all' scope, and explicitly states what is not included (mesoscale boundaries). It gives clear guidance on when to invoke this tool versus others.

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