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get_water

Read-onlyIdempotent

List the current app user's water intake entries for a date range. Requires X-App-User-Id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
date_toNo
date_fromNo

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds valuable context by disclosing the required X-App-User-Id header and the scoping to the 'current app user', which are not visible in the structured annotations. No contradiction exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and 19 words total. It front-loads the verb 'List' and includes only essential information: the resource, scope, and auth requirement. No unnecessary elaboration or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only tool, the description provides the core purpose, scope, and auth requirement, and annotations cover safety. However, it lacks detail on parameter semantics and the response format (no output schema), leaving the agent to guess what the entries look like. This makes it adequate but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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 for the bare parameters. It only mentions 'date range', which loosely suggests date_from/date_to are used for filtering, but it doesn't explain each parameter individually, their formats, or whether 'date' is a single date. This is insufficient to clarify the three undocumented params.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('List') on a clear resource ('water intake entries') with scope ('current app user' and 'date range'). It distinguishes itself from sibling tools like log_water by clearly indicating a read operation. This is exactly what a purpose statement should provide.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by saying 'current app user' and 'water intake entries', suggesting you'd use it to retrieve water intake data. However, it provides no explicit guidance on when to prefer this over alternatives, nor does it state any exclusions. The X-App-User-Id requirement is a prerequisite, not a usage guideline.

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

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TDQS

A3.7/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count3/5

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.

Completeness4/5

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.

Resources