Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Fitbit Insights
Fitbit fitness data integration. Use when the user wants fitness insights, workout summaries, step counts, heart rate data, sleep analysis, or to ask questions about their Fitbit activity data. Provides AI-powered analysis of fitness metrics.
skill openclawclawhub Free
Fitbit fitness data integration. Use when the user wants fitness insights, workout summaries, step counts, heart rate data, sleep analysis, or to ask questions about their Fitbit activity data. Provides AI-powered analysis of fitness metrics.
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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
- CLAWHUB-SUBMISSION.md, OVERVIEW.md, README.md, SETUP.md, SKILL.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. Then review README.md for any prerequisites, environment setup, or post-install checks. 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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- poisondminds
- Source page
- View original listing
- Canonical URL
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Documentation
Fitbit Fitness Insights
Get AI-powered insights from your Fitbit data. Query your fitness metrics, analyze trends, and ask questions about your activity.
Features
π Daily activity summaries (steps, calories, distance, active minutes) π Heart rate data and zones π΄ Sleep tracking and analysis π Workout/activity logs π Weekly and trend analysis π€ AI-powered insights and Q&A
Prerequisites
Requires: Fitbit OAuth access token Setup steps in references/fitbit-oauth-setup.md
Get Profile
FITBIT_ACCESS_TOKEN="..." python3 scripts/fitbit_api.py profile
Daily Activity
python3 scripts/fitbit_api.py daily [date] # Examples: python3 scripts/fitbit_api.py daily # Today python3 scripts/fitbit_api.py daily 2026-02-08 # Specific date Returns: steps, distance, calories, active minutes (very/fairly/lightly/sedentary), floors
Steps Range
python3 scripts/fitbit_api.py steps <start_date> <end_date> Example: python3 scripts/fitbit_api.py steps 2026-02-01 2026-02-07 Returns: total steps, average steps, daily breakdown
Heart Rate
python3 scripts/fitbit_api.py heart [date] Returns: resting heart rate, heart rate zones with minutes in each zone
Sleep Data
python3 scripts/fitbit_api.py sleep [date] Returns: duration, efficiency, start/end times, sleep stages
Logged Activities
python3 scripts/fitbit_api.py activities [date] Returns: workouts/activities logged (name, duration, calories, distance)
Weekly Summary
python3 scripts/fitbit_api.py weekly Returns: 7-day summary of steps and key metrics
AI Insights Usage
When user asks fitness questions, use the API to fetch relevant data, then provide insights: Example queries: "How did I sleep last night?" β fetch sleep data, analyze quality "Did I hit my step goal this week?" β fetch weekly summary, compare to goals "What was my average heart rate during workouts?" β fetch heart + activities, analyze "Am I more active on weekdays or weekends?" β fetch range data, compare patterns Analysis approach: Identify what data is needed Fetch via appropriate API command Analyze the data Provide insights in conversational format
Example Responses
User: "How did I do this week?" Agent: Fetch weekly summary Fetch recent sleep data Respond: "You had a solid week! Averaged 8,234 steps/day (up 12% from last week). Hit your 10k step goal 4 out of 7 days. Sleep averaged 7.2 hours with 85% efficiency. CrossFit sessions on Mon/Wed/Fri looking consistent!" User: "Did I exercise today?" Agent: Fetch daily activities Fetch daily activity summary (active minutes) Respond: "Yes! You logged a CrossFit session this morning (45 min, 312 calories). Plus 28 very active minutes total for the day."
Data Insights to Look For
Trends: Week-over-week changes, consistency patterns Goals: Compare to 10k steps, exercise frequency, sleep targets Correlations: Sleep quality vs activity, rest days vs performance Anomalies: Unusual spikes or drops Achievements: Personal bests, streaks, milestones
Token Management
The skill automatically loads tokens from /root/clawd/fitbit-config.json and refreshes them when expired (every 8 hours). Auto-refresh: Tokens are refreshed automatically - no manual intervention needed! Manual refresh (if needed): python3 scripts/refresh_token.py force Override with environment variable: export FITBIT_ACCESS_TOKEN="manual_token"
Error Handling
Missing token: Prompt user to set FITBIT_ACCESS_TOKEN API errors: Check token validity, may need refresh No data: Some days may have no logged activities or missing metrics See references/fitbit-oauth-setup.md for token management.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
5 Docs
- SKILL.md
- CLAWHUB-SUBMISSION.md
- OVERVIEW.md
- README.md
- SETUP.md