Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
health-sync
Analyze synced health data across Oura, Withings, Hevy, Strava, WHOOP, and Eight Sleep.
skill openclawclawhub Free
Analyze synced health data across Oura, Withings, Hevy, Strava, WHOOP, and Eight Sleep.
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, agents/openai.yaml, references/eightsleep.md, references/hevy.md, references/oura.md, references/setup.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.3.5
Provenance
- Publisher
- filipe-m-almeida
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Purpose
This skill is dedicated to analyzing the user's health data across available providers: Oura Withings Hevy Strava WHOOP Eight Sleep The main goal is to help the user understand trends, compare signals across providers, and find useful insights from their synced data.
Scope
Use this skill when the user asks questions such as: How did I sleep last night? How was my last workout? How did my resting heart rate change during the year? What trends are you seeing in my recovery, sleep, and training? What useful insights or next steps should I focus on?
Setup Handling (Remote Bootstrap Only)
Setup is bot-led and remote-first. The only supported onboarding flow is: Bot runs npx health-sync init remote bootstrap. Bot sends user: npx health-sync init --remote <bootstrap-token>. User sends back encrypted archive. Bot runs npx health-sync init remote finish <ref> <archive>. For full operational instructions, always consult: references/setup.md Do not use or recommend legacy direct setup flows such as: health-sync init as the primary user instruction health-sync auth <provider> as a standalone onboarding path Those commands may still exist for maintenance/debugging, but they are not the setup flow this skill should guide.
Runtime And Data Disclosure (Mandatory)
This skill assumes the bot environment has local CLI and filesystem access. Required binary: node npm npx Expected local working paths: workspace/health-sync/health-sync.toml workspace/health-sync/.health-sync.creds workspace/health-sync/health.sqlite Sensitive-data handling: Remote onboarding imports encrypted archives that contain provider credentials/tokens. Finish flow writes decrypted secrets to local files on the bot host. These files must be treated as sensitive at rest (access controls, backups, retention). Chat-safety boundary: Never ask users to paste raw secrets in chat. Only collect encrypted archive files via remote bootstrap flow.
Schema Handling
To understand data schemas and query correctly, read the provider reference files: references/oura.md references/withings.md references/hevy.md references/strava.md references/whoop.md references/eightsleep.md
Freshness Rule (Mandatory)
Before any analysis, always run: npx health-sync sync If sync fails, report the failure clearly and continue analysis only if the user explicitly asks to proceed with potentially stale data.
Analysis Workflow
Run npx health-sync sync first. Identify the user question and which provider/resource(s) are relevant. Read the provider schema reference before forming SQL. Query records, sync_state, and sync_runs as needed. Produce a clear, user-friendly answer with concrete numbers and dates. Highlight meaningful patterns and offer practical guidance. When data quality or coverage is limited, say so explicitly.
Output Style
Be concise, clear, and practical. Focus on useful interpretation, not just raw data dumps. Connect metrics to actionable insights (sleep, recovery, training, consistency, etc.). Ask follow-up questions only when necessary to improve analysis quality.
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
5 Docs1 Config
- SKILL.md
- references/eightsleep.md
- references/hevy.md
- references/oura.md
- references/setup.md
- agents/openai.yaml