sample_raster_values

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

No annotations are provided, so the description carries the burden; 'Read' implies a non-mutating operation, which is useful signal. However, it discloses nothing about side effects, cost, permission requirements, or how the limit/default interacts with layer sampling. An output schema exists, so return-value detail is not required here.

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?

A single front-loaded sentence with zero filler; the verb and the two-mode scope are established immediately.

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?

With an output schema covering return values and 100% schema coverage on parameters, the description is nearly sufficient. The remaining gap is precedence/conflict handling between 'points' and 'point_layer' and how 'limit' applies, which the agent must infer.

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 all six parameters described in the schema itself, so the baseline is 3. The description adds the mutually exclusive framing of 'points' vs 'point_layer' as two sampling modes, which is marginal but real value beyond the schema's field-level docs.

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 ('Read raster cell values') and names both input modes: map coordinates or a point layer's features. It does not explicitly distinguish itself from close siblings like zonal_statistics or get_raster_info, but the core purpose is unambiguous.

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 two sampling modes are stated, which implies when each parameter set is relevant, but there is no explicit guidance on when to use this over zonal_statistics (aggregation) or get_raster_info (metadata), nor any stated prerequisites. Usage is inferable rather than directed.

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