Log a cardio activity (run/bike/swim/etc.) for the current app user. Supports duration, distance, HR, power, calories.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | ||
| notes | No | ||
| sport | Yes | ||
| title | No | ||
| avg_hr | No | ||
| calories | No | ||
| distance_m | No | ||
| idempotency_key | No | ||
| duration_seconds | No |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| date | No | ||
| sport | No | ||
| distance_m | No | ||
| duration_s | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral context beyond what the annotations provide. It does not disclose what happens after logging (e.g., returns the created activity), any side effects, or validation behavior. The annotations already indicate it is a non-read-only, non-destructive operation, but the description contributes no further transparency.
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 brief and front-loaded: the first sentence states the purpose, and the second lists capabilities. It is appropriately sized, though the inclusion of 'power' is inaccurate and slightly undermines clarity.
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 tool with 9 parameters and no schema descriptions, this description is incomplete. It does not explain the date format, valid sport values, or required fields. The presence of an output schema means return values need not be described, but the parameter semantics are too sparse for reliable invocation.
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 0%, so the description must compensate, but it only mentions a few fields (duration, distance, HR, calories) and incorrectly includes 'power', which is not in the schema. It does not explain the required parameters (date, sport) or other optional fields like notes, title, or idempotency_key.
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's function: 'Log a cardio activity (run/bike/swim/etc.) for the current app user.' It uses a specific verb and resource, and the parenthetical examples distinguish it from strength workout logging tools like log_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 gives clear context by specifying the action (logging cardio) and scope (current app user), but it does not mention when to prefer this tool over alternatives or any exclusions. The distinction from log_workout is implicit through the term 'cardio'.
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.