Read workout sessions

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description adds genuinely useful behavioral context: ordering is 'most recent day first,' the tool returns session-level detail rather than daily totals, and it discloses a privacy implication about data becoming part of the conversation. These are meaningful traits not captured by the 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 front-loaded with the core definition, followed by structured usage guidance and a relevant privacy note. Every section earns its place: the first sentence states the tool's scope, the bullets give actionable routing rules, and the privacy note is important for local-vs-cloud model contexts. No filler is present.

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 rich annotations, full parameter schema coverage, and presence of an output schema, the description supplies all remaining context an agent needs: when to use it, when not to, how results are ordered, and what data is returned. The alternative tools are explicitly named, so the surrounding tool ecosystem is adequately addressed.

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 already documents limit, start_date, end_date, and activity_type fully. The description reinforces the overall intent but does not add parameter-specific detail beyond what the input schema provides, matching the baseline for full schema coverage.

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 a precise verb and resource: 'Read individual workout sessions,' and immediately disambiguates from the daily_metrics workout_minutes total. It also enumerates the meaningful fields returned (activity, timing, intensity, heart rate) and contrast with daily aggregates, making the tool's purpose unmistakable.

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 provides explicit 'Use this tool when' and 'Do not use this tool when' sections with concrete example queries and names the alternatives (read_health_data, get_metric_history). An agent can confidently route between this tool and its siblings without further inference.

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