crs_assign_by_guess

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

No annotations are provided, so the description fully discloses behavior: it is a heuristic, returns candidates with confidence and reason, and is not definitive. It mentions typical coordinate ranges, making the behavior transparent.

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 concise (about 6 lines) with no fluff. It starts with purpose, then input options, then output format, then usage advice. Every sentence adds value.

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 simplicity (2 optional params, output schema exists), the description covers all necessary aspects: purpose, inputs, output (candidates), and typical coordinate systems. It is complete for effective use.

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 has 0% description coverage for parameters, but the description explains that points should be a sample of [x,y] pairs and bbox should be [xmin, ymin, xmax, ymax]. This adds crucial meaning beyond the schema types.

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 guesses CRS from coordinate ranges, specifies inputs (points or bbox), and explains it returns ranked candidates. Sibling tools like crs_list_polish or crs_transform_point have different purposes, so this tool is distinct.

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 a concrete use case (unlabelled coordinates from old shapefiles) and advises confirming with the user. It doesn't explicitly say when not to use, but the context implies it's only for guessing.

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