Générer un plan d'entraînement personnalisé

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

No annotations are provided, so the description carries full responsibility. It explains what the tool generates (plan in 4 phases) and the two input modes. However, it does not disclose authentication requirements, whether the tool modifies any data, or error handling for invalid race_date (e.g., past date). The description is adequate but not thorough.

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, each serving a distinct purpose: overall function and phases, Strava mode, manual mode. It is front-loaded with the core purpose and structured logically. No redundant or vague sentences.

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 5 parameters (2 required), no output schema, and no annotations, the description covers the key modes and parameter interactions. It could mention what the plan includes (e.g., daily workouts), but the phases and mode choice are well explained. The return format is not described, but the tool likely outputs a plan object, and the context is sufficient for an AI agent.

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 coverage is 100%, so baseline is 3. The description adds significant value by explaining the interaction between goal_time and current_weekly_km, including the condition for bypassing Strava (manual mode). It also clarifies default behavior for goal_time when absent. This goes beyond the individual parameter descriptions.

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 generates a structured training plan from today to race day in four phases. It distinguishes two modes (Strava auto-calibrate vs manual) and specifies the resource (training plan) and verb (génère). This differentiates it from sibling tools like strava_weekly_workout or strava_predict_race_time.

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 guidance on when to use each mode: Strava mode (auto-calibrate from history) and manual mode (requires current_weekly_km + goal_time). It does not explicitly state when not to use the tool or contrast with alternatives like strava_predict_race_time, but the context is clear enough for most use cases.

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