find_ev_charging_stations

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention whether the operation is read-only, potential rate limits, authentication needs, or any side effects. The only behavior implied is a search/query, but without explicit disclosure, the agent lacks critical safety or operational context.

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: a clear purpose sentence, a brief explanation of functionality, a parameter breakdown, and a return value summary. Every sentence serves a purpose, and there is no redundant or fluff content. The length is justified given the parameter count and lack of other documentation.

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 (5 parameters, no output schema, no annotations), the description is remarkably complete. It covers the tool's purpose, usage context, all parameters with semantics, and the shape of the return value. There is no missing critical information for an agent to select and invoke this tool correctly.

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?

Schema description coverage is 0%, so the description must compensate fully. It does: the 'Args:' section explains each parameter with types, defaults, and examples (e.g., 'radius: Search radius in meters (defaults to 5000m/5km)' and 'connector_types: Optional list of specific connector types to filter by (e.g., ["type2", "ccs", "tesla"])'). This adds significant meaning beyond the raw 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's purpose: 'Locate electric vehicle charging stations near a specific location.' It uses a specific verb (locate/find) and resource (EV charging stations), and distinguishes itself from sibling tools like find_nearby_places or search_category by specializing in EV charging infrastructure.

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 on when to use the tool: 'Essential for EV owners planning trips or evaluating potential charging stops.' It does not explicitly mention alternatives or when-not-to-use, but the specialization makes the use case obvious. This is more than implied usage, so a 4 is appropriate.

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