dynamic_lisa

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

The description lists return values (sector counts, angles, vector lengths, p-values) but omits any behavioral traits such as whether it modifies data, required permissions, or error conditions. With no annotations, this is insufficient for a compute-heavy tool.

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 very concise (two sentences) and front-loaded with purpose. However, it comes at the cost of omitting parameter details, making it borderline inadequate for a tool with 10 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?

Given the high parameter count (10), 0% schema coverage, and no annotations, the description is grossly incomplete. It fails to explain any input parameters, leaving an agent with insufficient information to invoke the tool correctly.

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%, and the description provides zero information about any of the 10 parameters, including required ones like shapefile_path and value_columns. The verb 'Run' gives no clue about parameter roles or formats.

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 'Run dynamic LISA (directional LISA) with giddy.directional.Rose.' This clearly names the action, the specific spatial statistic, and the underlying function, distinguishing it from sibling LISA tools like moran_local.

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?

No guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description does not help an agent decide between dynamic_lisa and other spatial statistics tools like getis_ord_g_local or join_counts_local.

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