summarize_features

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

No annotations are provided, so the description carries the full behavioral burden. Beyond implying a read-only aggregation, it does not state whether it modifies data, permission requirements, limits/defaults, or any side effects, leaving meaningful behavioral gaps.

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 a single, front-loaded sentence with no waste. It immediately states the operation and then gives the practical purpose.

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?

The rich schema and existing output schema reduce what the description must cover, and it does communicate the core aggregation purpose. However, it omits routing guidance against the many statistics/selection/count siblings and provides no behavioral context despite missing annotations.

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 100%, so the schema already documents all six parameters, including group_by, value_field, where, limit, map_name, and layer_name. The description adds only a high-level mapping to 'one or more fields' and 'how much per category,' which is marginal beyond the 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?

The description states a specific operation: grouping rows by fields and aggregating, with the concrete use case of 'how many / how much per category.' It distinguishes itself from geoprocessing generally, but does not name or contrast against close siblings such as get_field_statistics, get_unique_values, or count_features.

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 implies when to use the tool by framing it as the 'fast way' to answer category-count/sum questions 'without geoprocessing,' which suggests an alternative to geoprocessing. However, it gives no explicit when-not conditions, prerequisites, or named alternative tools among the many summary/statistics siblings.

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