data_convert

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

Beyond the annotations, the description reveals meaningful behavior: automatic input detection, validation of results, and specific error reporting (self-intersections, out-of-range coordinates, removed RFC 7946 'crs' member). It also notes offline execution, which is useful operational context not present in annotations.

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 compact, starts with the core conversion action, and every sentence carries distinct value: format list, validation behavior, and real-world use cases. No filler or redundant restatement.

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?

For a three-parameter tool with full schema coverage and an output schema present, the description covers input formats, output format flexibility, validation behavior, offline operation, and typical usage scenarios. Nothing essential for correct invocation is missing.

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 100%, so the schema already documents data, to_format, and from_format thoroughly. The description adds general context about auto-detection and validation, but does not add parameter-level detail beyond what the schema already provides.

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 uses a specific verb ('Convert') with a clear resource ('geospatial data') and enumerates the supported formats, which immediately distinguishes this tool from coordinate-focused siblings like coord_convert and geometry-operation tools like geom_transform. The scope is precise and actionable.

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 gives clear applicable scenarios with concrete examples ('a customer sends KML, the routing engine wants an encoded polyline'), making it easy to know when to call this tool. It does not explicitly name sibling tools to avoid, but the format-conversion focus is distinct enough among the listed siblings.

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