compare_datasets

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds behavioral detail beyond that by specifying the structured output: whether data sets are identical, whether differences are in data or metadata, and the specific kinds of differences. It does not contradict the annotations.

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 sentences with no unnecessary words. The first sentence front-loads the core function and output; the second provides the key use case. It is concise, structured, and every clause earns its place.

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, output, and primary use case, and the output schema can define the return structure. However, given 0% schema parameter coverage, the optional `by` and `criterion` parameters are left unexplained, and there is no mention of SAS session prerequisites or behavior when the session is unavailable.

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%, so the description must compensate for parameter meaning. It clarifies that base and compare are the two data sets, but it gives no explanation of `by` or `criterion`. These optional parameters are left ambiguous despite being important for controlling how the comparison is performed.

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 uses a specific verb and resource: 'Run PROC COMPARE between two data sets' and clearly states what the tool returns: a structured diff with identity, data-vs-metadata distinction, and difference kinds. It distinguishes itself from sibling tools like run_sas and describe_dataset by focusing on comparison-based validation.

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 a clear primary use case: 'the primary way to validate that a rewrite produces the same result as the original.' This provides meaningful context for when to choose this tool, though it does not explicitly name alternatives or state when not to use it.

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