get_feature_count

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

With no annotations provided, the description carries the full burden. It mentions the optional where clause, which is a behavioral detail, but does not disclose other aspects such as read-only nature, performance implications, or potential errors. The simplicity of the tool makes this adequate, but it could be more explicit.

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 sentence, highly concise, and front-loaded with the core action. No wasted words; every word contributes to the meaning.

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 simple counting tool with an output schema present, the description is fairly complete. It specifies the operation and the optional filter. The output schema likely defines the return format, so that is covered. Missing are any usage conditions or edge cases, but the tool's simplicity mitigates this.

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. It explains the where_clause as an 'ArcGIS SQL where clause', adding semantic value. However, the dataset parameter is only implied by the phrase 'count features' and lacks explicit explanation of its meaning or format. Partial compensation for the missing schema descriptions.

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 'Count' and the resource 'features', making the tool's purpose unmistakable. It also distinguishes itself from siblings like query_features (which returns features) and describe_dataset (which describes structure) by focusing on the count operation.

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 gives no explicit guidance on when to use this tool versus alternatives. It does not mention conditions, prerequisites, or contrast with sibling tools like query_features or describe_dataset. The use case is implied but not spelled out.

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