Import training history

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

Annotations only state readOnlyHint=false and destructiveHint=false, giving minimal behavioral information. The description adds crucial details: active programs are validated server-side before anything is saved, and a response with ok=false and a violations list means nothing was written. This atomicity disclosure is valuable and goes beyond what annotations provide.

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 three sentences long, with the purpose front-loaded in the first sentence, prerequisites in the second, and failure behavior in the third. Every sentence provides necessary information without repetition or filler, making it dense yet efficiently organized.

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 complex tool with a large nested schema, the description covers the most critical preconditions (program approval, validation) and failure atomicity, but it omits practical details like how ids are handled (existing vs new records), whether the import merges or replaces data, and what a successful response implies. Since an output schema exists, return values are covered, but the missing upsert semantics and id behavior leave an agent somewhat uncertain about side effects.

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 the single 'document' parameter. It lists only four of the seven top-level sections (exercises, sessions, body metrics, programs) and omits 'schema_version' (a required field), 'athletes', 'day_templates', and 'metadata'. This incomplete mapping leaves agents to infer the full document structure from the schema alone, with little guidance on key prerequisites like schema_version.

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 opens with 'Bulk-import a full workout document (exercises, sessions, body metrics, programs)', stating a specific verb, resource, and scope. This clearly differentiates it from sibling tools like log_session and log_body_metric, which handle single entities. The word 'full' signals the tool's bulk nature.

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 concrete prerequisite: programs must be designed via get_coaching_context(task='new_program') and explicitly approved by the user before importing. It also names review_program_draft as the validation reference, providing context on when this is appropriate. It implies the bulk-vs-single distinction through its opening phrase, though it doesn't explicitly enumerate when to use alternatives.

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