tp_workout_analysis

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

The description discloses the output (derived metrics) but does not explicitly state that the tool is read-only, requires authentication, or has any side effects. Given no annotations, the description partially fulfills the transparency burden but leaves behavioral gaps.

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 concise: one sentence for purpose, then clear args and returns sections. No redundant information, every sentence adds value.

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 single-parameter analysis tool with an output schema, the description adequately explains inputs and outputs. It doesn't mention authentication or error conditions, but those are reasonable defaults given the sibling context; the output schema likely covers return structure.

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?

The only parameter (workout_id) is explained with the phrase 'The TrainingPeaks workout ID,' adding context beyond the schema's title 'Workout Id.' This helps the agent understand what value to provide, though format details (e.g., numeric) are implicit.

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 clearly states the tool performs 'deep analysis' of a specific workout and explicitly lists derived metrics (efficiency factor, variability index, intensity distribution, comparison context), distinguishing it from raw workout retrieval tools like tp_get_workout.

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 usage for analysis vs. raw data but provides no explicit guidance on when to use this tool over siblings like tp_performance_summary or tp_fitness_trend, nor does it mention prerequisites.

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