statistics_analysis

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

No annotations are provided, so the description must cover behavioral traits. It correctly states that the tool 'Reads an input table and writes a new output table,' implying it is read-only on the input and creates a new output. However, it does not disclose potential side effects, required permissions, or overwrite behavior beyond what is in the schema (e.g., the overwrite parameter is schema-only). The description is adequate but not comprehensive.

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 with three sentences, each serving a clear purpose: stating the action, providing usage context, and noting input/output. It front-loads the primary purpose. Minor improvements could include bullet points for statistics types, but overall it is well-structured and compact.

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 a detailed input schema and an output schema (per context), the description provides sufficient context for the agent to understand the tool's role. It explains the overarching operation and use case. However, it could be more complete by mentioning that the output is a new table with summarized fields.

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 does not reference any parameters or their meanings, despite the schema having detailed descriptions. With schema description coverage at 0%, the description must compensate but fails to do so. The agent must rely solely on the schema for parameter understanding, which is sufficient but the description adds no value.

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's purpose: 'Calculate summary statistics for numeric or categorical fields using ArcPy Statistics.' It uses a specific verb ('calculate') and resource (summary statistics), and mentions common use cases (aggregating counts, sums, means, etc.). The purpose is unambiguous and distinguishes itself from sibling tools like frequency_analysis by specifying the exact statistical operations.

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 provides a usage context: 'Use this to aggregate... before reporting or joining results back to features.' However, it does not include explicit guidance on when not to use this tool or how it differs from alternatives like frequency_analysis or summarize_within. The usage guidelines are implied but lack clarity on exclusions.

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