meta interpret experiment results

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so no contradiction exists. The description adds that this is an interpretive/analytical read rather than a raw fetch, which is useful, but it does not disclose details like how missing studyId maps to adAccountId discovery or any rate-limit behavior.

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 a single compact sentence with the core action front-loaded before the qualifying detail. The tail is a slightly dense list, but every phrase 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?

Given the annotations, an output schema, and fully described parameters, the description is nearly complete. It could improve by clarifying how this 'interpret' tool relates to meta_get_study_results or what form the interpretation takes, but an agent can select and call it safely with the current information.

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 100%, so the schema fully documents limit, studyId, adAccountId, cellEntityType, and includeCellEntities. The description's mention of 'cells, objectives, and optional cell entities' loosely maps to cellEntityType/includeCellEntities, but it adds no information beyond what the input schema already provides.

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?

Description names a concrete verb-resource pair: 'Read and interpret A/B test or conversion lift study results,' and lists relevant facets (confidence guardrails, cells, objectives, optional cell entities). This is clearer than the bare title and distinguishes it from raw study-fetching siblings, though it doesn't explicitly contrast with meta_get_study_results.

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 implies the intended scenario: interpreting experiment study results rather than merely fetching them. It does not explicitly name alternatives (e.g., meta_get_study_results for raw results) or give when-not-to-use guidance, but the phrase 'A/B test or conversion lift study results' provides enough context for an agent to infer the primary use.

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