ab_test_analyze

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

Despite no annotations, the description provides a comprehensive 'Behavioral Transparency' section covering side effects (read-only, stateless), authentication, rate limits, error handling, idempotency, and data privacy. This fully compensates for missing 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?

The description is well-structured with clear sections but contains redundancy (e.g., 'read-only and stateless' repeated) and a vague 'When to use' that could be more concise. Some sentences could be trimmed without losing meaning.

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?

For a tool with 6 parameters, no output schema, and no annotations, the description covers all essential aspects: input explanation, return values (winner, z-score, etc.), side effects, rate limits, authentication, error handling, and data privacy. It is fully adequate for an AI agent to use 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?

The schema has 0% coverage, but the description includes an 'Args:' block that explains each parameter except 'api_key', which is covered in the behavior section. This adds significant meaning beyond the raw schema, though the api_key parameter could be more explicitly linked.

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 it analyzes A/B test results with statistical significance testing and lists specific outputs (winner, z-score, p-value, etc.). This is a specific verb+resource and distinguishes itself from sibling tools focused on other marketing tasks.

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 includes explicit 'When to use' and 'When NOT to use' sections, providing context for appropriate usage. However, the 'When to use' statement is too generic and does not directly compare to sibling tools, though the siblings are clearly different in function.

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