features_get

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

With no annotations, the description carries full transparency burden. It discloses that limit defaults to 5 and is capped at 20, and that geometry is omitted unless 'include_bbox' is set. These are key behavioral traits, though more details (e.g., error handling) could be added.

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—two sentences that pack essential information. It front-loads the main action and then provides critical details about limits and geometry, with no wasted words.

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 and presence of an output schema, the description covers the key points: purpose, limit cap, geometry omission, and sibling comparison. It doesn't discuss error cases or prerequisites, but for a preview tool this is adequate.

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 add meaning. It explains the limit default and cap, and the role of include_bbox for geometry. However, it does not elaborate on filter_expression format or layer_id beyond being required, leaving some gaps.

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 verb 'Fetch' and resource 'features from a vector layer', with an optional filter. It distinguishes itself from the sibling 'get_layer_sample' by explicitly comparing and noting it's a preview, not a data export.

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 explicitly compares to 'get_layer_sample', indicating this tool is for previews and not data export. This provides clear context for when to use it, though it doesn't list all alternatives or explicit when-not-to-use conditions beyond the comparison.

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