adbscan

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

No annotations are provided, so the description carries full burden. It fails to disclose behavioral traits such as what 'adaptive' means, how parameters like eps and min_samples affect clustering, or any data quality requirements. The output schema exists but behavioral details beyond return format are absent.

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, front-loading the essential purpose and constraints. It is concise but very brief; while efficient, it lacks structural elements like bullet points or separate sections that could improve readability for a tool with 6 parameters.

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?

Despite having an output schema, the description fails to explain the adaptive nature of DBSCAN, expected input geometry, or parameter interplay. With 6 parameters and a moderately complex algorithm, the description is too sparse to enable confident usage without external knowledge.

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 0%, yet the description only adds value for one parameter: dependent_var should not be provided. No other parameters (shapefile_path, target_crs, distance_threshold, eps, min_samples) are explained, leaving the agent without guidance on their meaning or usage 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 clearly states the tool performs 'Adaptive DBSCAN clustering', with specific constraints 'requires coordinates, no dependent_var'. The verb 'clustering' and the resource 'Adaptive DBSCAN' differentiate it from siblings, as no other tool in the list mentions clustering algorithms.

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 implicitly guides usage by stating prerequisites (coordinates) and a constraint (no dependent_var), but does not explicitly mention when not to use or suggest alternatives. Given the specialized nature, it provides clear context for appropriate invocation.

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