normalize_geometry

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

With no annotations, the description carries full burden. It mentions using shapely.normalize and output format but does not clarify if the operation is destructive or if it might modify the geometry in place. Basic transparency but lacks details on side effects.

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 extremely concise with three sentences covering purpose, parameter, and returns. Front-loaded with action verb and essential info, no waste.

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 low complexity and presence of an output schema, the description is mostly complete: it explains input, process, and output. Could mention error handling for invalid WKT, but overall sufficient.

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 only parameter 'geometry' is described as a WKT string, adding meaning beyond the schema's type-only definition. However, no additional constraints or examples are provided, though it is sufficient for a single-param tool.

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 normalizes geometry orientation/order using shapely.normalize, with specific input (WKT) and output (dict) details. It distinguishes itself from sibling tools like 'is_valid' or 'make_valid' by focusing on normalization.

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?

No explicit guidance on when to use this tool instead of alternatives. The description implies use for normalizing geometry order but does not mention when not to use or provide context about related tools.

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