get_training_load_breakdown

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

No annotations are provided, so the description carries the full burden, and it does disclose the composition of the response (minutes, percentage distribution, acute/chronic load, ACWR, TSB as of the end date). However it says nothing about permissions, data availability limits, or whether the computation is expensive/slow — gaps for a tool with zero annotation coverage.

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 payload sentence is front-loaded and the Args block is compact and purposeful given the empty schema descriptions. Slightly redundant to enumerate return values when an output schema exists, but it is not verbose.

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?

An output schema exists so return values need not be explained (though they are, harmlessly). With no annotations, the description covers date formats and the analytical content well; only the lack of sibling differentiation and edge-case behavior keeps it from being fully 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?

Schema description coverage is 0%, so the schema contributes nothing about the two date parameters. The description compensates by documenting both start_date and end_date with the exact YYYY-MM-DD format, and clarifies that end_date anchors the ACWR/TSB computation. It does not explain behavior for inverted or very long ranges, but the core semantics are covered.

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?

States a specific verb ('Get') and resource ('training load breakdown by sport') with scope ('for a date range'), which is far more informative than the bare name. It partially distinguishes itself from near-siblings like get_training_load_balance and get_training_load_trend by saying 'breakdown by sport', but never explicitly contrasts with them.

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?

There is no when-to-use guidance, no prerequisites, and no mention of the closely related training-load siblings (trend, balance, weekly progression). The agent must infer usage entirely from the description of returned data.

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