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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so the safety profile is covered. The description adds that results include sample values alongside types, which is genuine behavioral context. It says nothing about result size, or whether a layer with many columns is truncated, so a 3 is warranted given annotations do the heavy lifting.

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?

Three short sentences, front-loaded with the verb and the returned fields, then the timing guidance, then the rationale. Every sentence carries distinct information and none restates the tool name.

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 single-parameter read tool with no output schema, the description successfully conveys what the return contains (column names, types, sample values). The only gap is absence of any note on output volume or limits, which matters for layers with many columns.

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?

Only one parameter, layer_id, and the schema documents it at 100% coverage with concrete example IDs (lgd_states, airports, wards_chennai). The description adds no syntax or format detail beyond the schema, so the high-coverage baseline of 3 applies.

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?

States a specific verb and resource: 'Get column names, types, and sample values for a layer.' That is far more informative than the name alone and implies a schema-introspection result, though it never explicitly contrasts with close siblings like get_layer_detail, which an agent may also plausibly reach for.

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?

Gives an explicit sequencing instruction: 'Use BEFORE querying to discover what columns exist.' That clearly signals the discovery step that precedes query_layer. It stops short of naming alternatives or stating when this tool is unnecessary.

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