frequency_analysis

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

With no annotations, the description carries full burden. It discloses that the tool reads an input table and writes a new output table, must use PathGuard allowed roots, and that overwrite=true is needed for existing outputs. However, it does not mention error handling, performance implications, or license requirements.

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 two concise sentences plus one additional sentence. It is front-loaded with the purpose, immediately followed by use cases and then a constraint. Every sentence adds value and there is 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?

The description covers the tool's purpose, typical usage, and key behavioral constraints (input/output, PathGuard, overwrite). It does not detail the output table structure (e.g., fields: combination fields + frequency count), but the output schema is noted as existing which should fill that gap. For a simple frequency-counting tool, this is largely complete.

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 input schema already provides detailed descriptions for all four parameters (in_table, out_table, overwrite, frequency_fields). The description adds only overarching context (e.g., 'using ArcPy Frequency', PathGuard) but does not enrich parameter meanings beyond what the schema provides. With schema coverage effectively 100%, the baseline 3 is appropriate.

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 counts unique combinations of attribute values via ArcPy Frequency. It specifies the action (count), resource (attribute values), and method (ArcPy Frequency). This distinguishes it from sibling tools like statistics_analysis or summarize_within which aggregate differently.

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 gives explicit use cases: profiling categorical fields, detecting duplicates, summarizing classes, and preparing frequency tables for QA/QC and reporting. It implies when to use but does not mention when not to use or list alternative tools, which would raise the score to 5.

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