Intervals.icu MCP Server

update_wellness_bulk

Create or update multiple days of wellness data in one validated call. Rejects the entire batch if any entry is invalid, so partial writes never occur.

Instructions

Create or update multiple days of wellness data in a single call.

Writes to PUT /athlete/{id}/wellness-bulk. Each entry is a dict with a ``date``
(YYYY-MM-DD) plus any of the same fields as update_wellness: weight, resting_hr,
hrv, sleep_hours, sleep_quality, calories_consumed, carbohydrates, protein, fat,
hydration_volume, hydration_score, soreness, fatigue, stress, mood, motivation,
injury, comments, locked. Pass -1 to clear a numeric field. Every date is
validated up front — if any entry is invalid the whole batch is rejected, so
there are no partial writes.

Args:
    entries: List of per-day wellness dicts, each with a ``date`` and one or more fields.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entries": "<entries>"
    },
    "name": "update_wellness_bulk"
  }
}

Input Schema

Name	Required	Description	Default
`entries`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Nov 2, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does well: it names the write endpoint (PUT .../wellness-bulk), discloses that every date is validated up front, and states that the whole batch is rejected with no partial writes. It omits auth/scope requirements and rate-limit behavior, which keeps it from a 5.

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

Conciseness4/5

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

Front-loaded with the purpose, then endpoint, semantics, and the all-or-nothing guarantee in order of importance. The field list is long but earns its place; the trailing 'Args:' line largely restates the earlier sentence about entries, which is minor redundancy.

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

Completeness4/5

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

For a mutation tool with no annotations, the description covers atomicity, field semantics, and the clear-field sentinel — and an output schema exists so return values need no explanation. Missing only permission/scope expectations and behavior of the 'locked' flag, minor gaps rather than blocking ones.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the single parameter is an opaque array of free-form objects, so the description must compensate — and it does, enumerating every accepted field, requiring a YYYY-MM-DD 'date' key, and documenting the -1 sentinel for clearing numeric fields. This is meaning well beyond anything the schema conveys.

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 opens with a specific verb and resource — 'Create or update multiple days of wellness data in a single call' — and the 'bulk'/'multiple days' framing distinguishes it from the singular update_wellness sibling. An agent can tell exactly what it does without opening the schema.

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

Usage Guidelines4/5

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

The 'call' and 'multiple days' wording implicitly tells the agent to use this over update_wellness when handling more than one day, and the reference to update_wellness clarifies where per-field semantics come from. There is no explicit 'use X when' routing statement or prerequisite list, so it stops short of a 5.

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