describe_layer

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

No annotations are supplied, so the description carries the full burden and does disclose the observable output surface in detail (row counts, extents, value distributions). It never states it is a read-only operation, nor whether it is expensive on large layers, which would be the main risk an agent needs to know.

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?

Two sentences, no filler: the return contents come first, the sequencing advice second. Every clause carries information an agent would otherwise have to infer.

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 two-parameter read tool with no output schema, the definition is close to self-sufficient because it enumerates the response shape. The remaining gap is operational: no mention of cost on large layers or behavior when the layer name doesn't exist.

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 coverage is 100%, with both 'layer' and 'include_value_samples' documented inline. The description adds a little meaning by explaining what the value samples consist of (common text values, numeric min/max), but it never names the toggle parameter itself, so it stays at the baseline for a fully documented 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?

States a specific verb and resource ('Describe one layer') and then enumerates exactly what is returned: columns and types, row count, extent, geometry types, text value frequencies, numeric min/max. This is clearly distinct from list_layers (enumeration) and sample_features (row sampling), so an agent can select it without opening the schema.

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?

Explicitly prescribes ordering: 'Call this BEFORE filtering so you use real column names and values.' That is strong when-to-use guidance. It stops short of naming alternatives or stating when-not to use it (e.g., for a quick column-only listing).

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