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

Annotations already declare readOnlyHint=true and destructiveHint=false, so no contradiction. The description adds rich behavioral detail beyond annotations: default bucket selection yields ~150 rows, fine buckets over the whole ride are widened to ~300 rows and the header notes it, and the 'moving clock' semantics tie to get_activity blocks and lactate sample t. It also states the output is CSV, which is not in the schema. This fully discloses expected 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 dense but every sentence earns its place. It opens with the core purpose, then usage rationale, then parameter semantics, then a practical anti-pattern. It is front-loaded and well-organized, with no filler or redundant statements. Length is justified by the complexity of the zoom behavior.

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 read-only data-retrieval tool with 4 parameters (1 required) and no output schema, the description is complete. It explains the return format (CSV), the columns, default row counts, the zoom mechanism, and the clock reference. It also covers when to use it and how it differs from related tools. Nothing an agent needs to invoke it correctly is missing.

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?

Although schema description coverage is 100%, the description adds substantial meaning beyond the schema. It explains that fromSec/toSec use the same clock as a block's start and a lactate sample's t, and that bucketSec interacts with them to zoom into a rep or climb. It also explains the default row-count behavior and the widening fallback. These semantics are not in the schema and are essential for correct parameter usage.

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 states a precise verb-resource pair: returns the activity's own chart as a time-bucketed CSV of average power, heart rate, cadence, and altitude. It distinguishes itself from siblings by explicitly positioning it as the 'SEE the session' tool versus a summary, and even contrasts it with get_activity by referencing the same clock. An agent can tell exactly what this does and how it differs from get_activity or other data tools.

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?

Provides explicit when-to-use guidance: 'Call it when a summary is not enough and you need to SEE the session.' It also gives a concrete anti-pattern: 'Prefer this over asking the athlete for a screenshot.' For zooming, it explains exactly when to pass fromSec/toSec with a small bucketSec. This is model-level guidance with clear alternatives and conditions.

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