oura

$npx mdskill add vellum-ai/vellum-assistant/oura

Pull sleep and activity data from Oura Ring API for analysis

  • Connects to OAuth-protected Oura Ring device via Vellum's credential proxy.
  • Deploys requests to Oura Cloud API V2 using specified access token credentials.
  • Extracts detailed health metrics including sleep, activity, and heart rate data.
  • Delivers processed health insights for further analysis or presentation.

SKILL.md

.github/skills/ouraView on GitHub ↗
---
name: oura
description: Pull sleep, activity, readiness, heart rate, and other health data from a connected Oura Ring via the Oura Cloud API V2
compatibility: "Designed for Vellum personal assistants"
metadata:
  emoji: "💍"
  vellum:
    category: "health"
    display-name: "Oura Ring"
    includes:
      - oura-setup
---

# Oura Ring — Data Access

Pull sleep, activity, readiness, heart rate, and other health data from a connected Oura Ring via the Oura Cloud API V2.

**For initial setup (OAuth, app registration, token exchange), see the `oura-setup` skill.**

## Prerequisites

- Oura Ring already connected via OAuth (see `oura-setup` skill)
- Credential stored: `oura` / `access_token` with injection template for `api.ouraring.com` (Authorization header, Bearer prefix)
- Credential ID can be found via `credential_store` list action, filtering for service `oura`, field `access_token`

## Making Requests

All requests go through the credential proxy — no need to manually attach tokens.

```bash
curl -s "https://api.ouraring.com/v2/usercollection/{endpoint}?start_date=YYYY-MM-DD&end_date=YYYY-MM-DD"
```

Run via `bash` with:

- `network_mode: "proxied"`
- `credential_ids: ["<oura access_token credential_id>"]`

## Endpoints

| Endpoint             | What It Returns                                                          | Best For               |
| -------------------- | ------------------------------------------------------------------------ | ---------------------- |
| `personal_info`      | Age, weight, height, email                                               | Connection test        |
| `daily_sleep`        | Sleep score, duration, efficiency, stages                                | Morning check-in       |
| `sleep`              | Detailed sleep periods — HR, HRV, movement, timestamps                   | Deep sleep analysis    |
| `daily_readiness`    | Readiness score, HRV balance, recovery index                             | Morning readiness      |
| `daily_activity`     | Steps, calories, movement, MET data, activity score                      | Daily activity summary |
| `heartrate`          | Continuous HR readings (uses `start_datetime`/`end_datetime` ISO format) | Workout HR, resting HR |
| `workout`            | Detected workouts — HR, calories, duration, type                         | Exercise tracking      |
| `daily_spo2`         | Blood oxygen (SpO2) nightly average                                      | Breathing/oxygen       |
| `daily_stress`       | Stress score, recovery periods                                           | Stress monitoring      |
| `ring_configuration` | Ring model, firmware, color, design                                      | Ring info              |

## Query Parameters

- **Most endpoints:** `start_date` and `end_date` in `YYYY-MM-DD` format
- **Heart rate:** Uses `start_datetime` and `end_datetime` in ISO 8601 format (e.g. `2025-01-15T00:00:00-05:00`)
- **Personal info / ring config:** No date params needed
- Omitting dates usually returns recent data (last 1-7 days depending on endpoint)

## Common Patterns

### Morning health check

Pull sleep + readiness + activity for today:

```bash
DATE=$(date +%Y-%m-%d)
curl -s "https://api.ouraring.com/v2/usercollection/daily_sleep?start_date=$DATE&end_date=$DATE"
curl -s "https://api.ouraring.com/v2/usercollection/daily_readiness?start_date=$DATE&end_date=$DATE"
```

### Workout details with HR

```bash
YESTERDAY=$(date -v-1d +%Y-%m-%d)
TODAY=$(date +%Y-%m-%d)
curl -s "https://api.ouraring.com/v2/usercollection/workout?start_date=$YESTERDAY&end_date=$TODAY"
```

### Heart rate during a specific window

```bash
# Adjust the datetime range as needed (ISO 8601 with timezone offset)
curl -s "https://api.ouraring.com/v2/usercollection/heartrate?start_datetime=YYYY-MM-DDT23:00:00-05:00&end_datetime=YYYY-MM-DDT01:00:00-05:00"
```

## Notes

- New rings need **1-2 nights** to calibrate before sleep/readiness scores are meaningful
- Sleep data appears a few hours after waking
- Short workouts (<15 min) may not be auto-detected — check raw heart rate instead
- Heart rate endpoint can return large datasets — keep time windows tight
- Rate limit: 5,000 requests per 5 minutes
- Tokens expire after ~30 days. Refresh using the `oura-setup` skill's token refresh instructions.

## Token Refresh

When the access token expires, use the refresh token via the `oura-setup` skill:

```bash
curl -s -X POST "https://api.ouraring.com/oauth/token" \
  -d "grant_type=refresh_token&refresh_token=REFRESH_TOKEN&client_id=CLIENT_ID&client_secret=CLIENT_SECRET"
```

Store the new access_token and refresh_token. See `oura-setup` for full details.

More from vellum-ai/vellum-assistant

SkillDescription
acpSpawn external coding agents via the Agent Client Protocol (ACP)
amazonShop on Amazon and Amazon Fresh through your browser
api-mappingRecord and analyze API surfaces of web services
app-builderBuild and edit small, personal visual tools and artifacts — dashboards, trackers, calculators, data visualizations, charts, simple landing pages, and slide decks the user wants for THEMSELVES. This is the right skill whenever the user asks to "visualize this," "make a chart," or "build an artifact" for their own use, or to edit an app they already built here. Do NOT reach for a ui_show dynamic_page to fake an artifact — build a real persistent app here. NOT for complex, multi-user, or shippable products — those go to a real project folder with a coding agent (see Scope below).
app-controlDrive a specific named macOS app via raw input bypassing the Accessibility tree
assistant-migrationMigrate from ChatGPT, Claude, OpenClaw, Hermes, Manus, and other AI assistants into Vellum by inspecting their data exports, conversation archives, files, prompts, custom instructions, memory, saved memories, tools, GPTs, workflows, integrations, and relationships, then mapping as much as safely possible into Vellum primitives. Handles single-source and multi-source migrations with a unified, deduplicated inventory.
chatgpt-importImport conversation history from ChatGPT into Vellum
cli-discoverDiscover which CLI tools are installed, their versions, and authentication status
contactsManage contacts, communication channels, access control, and invite links
conversation-launcherOffer the user several spin-off conversations as clickable buttons on a single persistent card. Each click spawns a fresh seeded conversation in the sidebar; the user keeps their place in the current conversation. Use when you want to branch into N focused threads (research directions, draft choices, pending replies, triage of N items) without losing the current context. Not for single-destination pivots — just reply inline.