Schedule the signed-in user's routine into planned workouts from start_date. Coach assignment of another user is REST-only.
| Name | Required | Description | Default |
|---|---|---|---|
| routine_id | Yes | ||
| start_date | Yes | YYYY-MM-DD | |
| cadence_days | No | ||
| idempotency_key | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly=false, idempotent=false, destructive=false, so the description only needs to add extra behavioral context. It does add scope/auth guidance by saying 'signed-in user' and 'REST-only', but it does not disclose side effects such as whether existing planned workouts are overwritten, how cadence is applied, or whether the operation can fail due to conflicts.
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?
Two short sentences, the first states the core action and the second provides a scope limitation. No redundant phrases, front-loaded with the main verb and object.
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 mutation tool with 4 parameters and no output schema, the description is too thin. It does not explain cadence behavior, idempotency semantics, what happens if the routine already has planned workouts, or any error conditions. The REST-only note helps but leaves major behavioral gaps.
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 only 25% (start_date has format). The description mentions the routine and start_date ('signed-in user's routine', 'from start_date'), but does not explain cadence_days or idempotency_key, and does not map routine_id to the parameter. With low schema coverage, the description should compensate more than it does.
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 uses the specific verb 'Schedule' with clear resources: 'the signed-in user's routine' into 'planned workouts', starting from a date. It distinguishes the tool from siblings like get_routine and list_routines by indicating this is a write operation that creates planned workouts from a routine, and the REST-only note clarifies a related but unsupported path.
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 states explicitly that coach assignment of another user is REST-only, which tells the agent when not to use this tool and provides the alternative (REST API). It also scopes usage to the signed-in user's routine and gives the start condition ('from start_date').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes (meals, workouts, routines, body metrics, etc.). A few pairs like get_progress and get_muscle_recovery overlap in data but differ in usage, and the AI tools are separated by input type. Overall, an agent can reliably select the right tool.
Tool names predominantly follow a verb_noun snake_case pattern (get_, log_, update_, delete_, search_, list_). The ai_* prefix is consistent but includes noun-like names (ai_meal_plan, ai_photo_macros) that deviate slightly from verb-first convention. Still predictable and readable.
With 36 tools, the server exceeds the typical 'heavy' threshold, but the scope is broad covering meals, workouts, routines, metrics, AI features, and data sync. Each tool serves a distinct capability, so the count is justified though on the higher end.
The server provides solid lifecycle coverage for core resources: meals (create/read/update/delete), workouts (log/get/delete, set updates), body metrics (get/log with profile upsert), routines (list/get/instantiate), and exercise lookup (search/resolve/list). Minor gaps exist for updating/deleting cardio and water entries, but they are not critical.