describe_dataset

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

Annotations already mark the tool as read-only and idempotent, so the description adds extra behavioral context: per-layer description for containers, the refusal of operations on unchosen layers, the [raster] extra requirement, and the distinction between nodata and masked statistics. No contradiction exists.

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 longer than average but well-structured with clear vector/raster sections and front-loaded purpose. Each sentence adds useful behavior or usage context, though it could be tightened without losing 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 complexity and the presence of an output schema, the description covers the important edge cases: multi-layer containers, raster-specific requirements, nodata handling, and when to extract a layer first. It is complete enough for an agent to decide when and how to invoke it correctly.

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 0%, so the description must compensate, but it never explicitly names or describes the single required parameter. It implicitly refers to a 'dataset' and uses 'path' in the run_sql example, yet an agent still lacks clear semantics about the expected argument format, type, or identifier.

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 opens with a specific verb and resource: 'Inspect a dataset, vector or raster, before analysing it.' It clearly distinguishes the tool's scope from siblings by detailing vector, raster, and multi-layer container behavior, so an agent can tell it apart from related GIS tools.

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?

It explicitly says to call this tool first on any uninspected dataset and warns that silent GIS errors often stem from wrong assumptions. It also provides a concrete follow-up action for multi-layer containers, naming run_sql with an example query, which gives strong when-to-use and when-to-do-something-else guidance.

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