get_feature_count

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

No annotations provided, but the description clarifies it is read-only ('does not modify data') and operates within PathGuard allowed roots. This adds important behavioral context beyond the name.

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 concise (three sentences) and well-structured, starting with the core purpose and then providing usage guidance and behavioral notes. Every sentence adds 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 simplicity and the presence of an output schema (not shown but indicated), the description adequately covers purpose, usage, parameters, and behavior. No gaps are apparent.

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?

The single parameter 'dataset' is thoroughly described: it explains the expected input types (feature class, table, raster, geodatabase item) and security constraint (PathGuard allowed root). This compensates for the 0% schema description coverage.

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 explicitly states 'Return the row or feature count for an existing dataset' and positions it as a lightweight validation step. This clearly distinguishes it from sibling tools that perform more complex analyses.

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 advises using it 'before and after geoprocessing, filtering, import, export, or QA/QC workflows', providing clear usage context. It lacks explicit alternatives but is sufficient.

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