Export the signed-in user's data as JSON. Pass domains (e.g. meals,workouts) or confirm:true for a full copy. Identity comes from the token, never a caller-supplied user id.
| Name | Required | Description | Default |
|---|---|---|---|
| confirm | No | Required true for a full dump when domains is omitted. | |
| domains | No | Comma-separated subset, e.g. 'meals,workouts'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and closed-world behavior. The description adds valuable context about identity coming from the token and never caller-supplied, which is a security-related behavioral trait not covered by annotations. It also clarifies the return format as JSON and the full-copy semantics, enhancing transparency beyond the structured fields.
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 two sentences, front-loaded with the primary purpose, and each clause earns its place. It includes necessary usage details without redundant filler.
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 tool's simplicity (2 params, 100% schema coverage, no output schema), the description covers the key aspects: the export function, parameter modes, and auth source. Minor gaps include behavior when neither parameter is provided and whether both can be passed together, but overall it is sufficiently complete for an 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% with descriptions for both parameters. The description adds meaning by explaining the relationship between `domains` and `confirm` as alternatives ('Pass `domains` ... or confirm:true'), which is not immediately clear from the schema alone. It also provides concrete examples ('meals,workouts').
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 purpose: 'Export the signed-in user's data as JSON.' The verb 'export' is specific, and the resource is defined as the user's data. It also distinguishes itself from sibling get_* tools by offering bulk export rather than individual record retrieval.
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 usage instructions by explaining the two modes ('Pass `domains` ... or confirm:true for a full copy'), but it does not explicitly state when to choose this tool over alternatives like get_meals or get_workouts. The context implies bulk export, but there is no direct comparison or exclusion of sibling tools.
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.