directional_distribution

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

No annotations are provided, so the description must disclose behavioral traits. It states that the tool writes a new output feature class without modifying inputs, but lacks details on prerequisite input geometry type (points) or projection requirements. Adequate but not thorough.

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?

Two concise sentences: first defines the tool's action and resource, second adds usage guidance and constraints. No redundancy or fluff.

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 moderate complexity and the presence of an output schema, the description covers key aspects: purpose, supported parameters, and non-destructive nature. However, it omits details like input geometry constraints (points) and output field contents.

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 description mentions ellipse_size and weight_field, but the input schema already provides complete descriptions for all parameters. With 0% schema coverage claimed, the description adds minimal value beyond what is already in 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?

Clearly states it creates standard deviational ellipse features using ArcPy DirectionalDistribution, and lists specific use cases like point-pattern analysis and movement corridors. This distinguishes it from sibling tools like mean_center or hotspot_analysis.

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?

Provides explicit use cases and mentions supported options (ellipse_size, weight_field) and non-modifying behavior. However, it does not explicitly state when not to use this tool or mention alternative tools for similar tasks.

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