Stride Analysis Patterns
Helps with analysis, patterns as part of agent workflows workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add stride-analysis-patterns npx -- -y @trustedskills/stride-analysis-patterns
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"stride-analysis-patterns": {
"command": "npx",
"args": [
"-y",
"@trustedskills/stride-analysis-patterns"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The stride-analysis-patterns skill enables AI agents to analyze and interpret patterns in stride data, such as gait analysis or movement sequences. It can identify anomalies, detect trends over time, and provide insights into biomechanical efficiency or potential injury risks based on the input data.
When to use it
- To assess athletic performance by analyzing running or walking patterns.
- For medical professionals evaluating patients with mobility issues.
- In fitness applications that track user movement for personalized training recommendations.
- During rehabilitation programs to monitor progress and adjust therapy plans.
Key capabilities
- Detection of irregular gait patterns
- Trend analysis over time intervals
- Identification of biomechanical inefficiencies
- Integration with motion sensor or wearable device data
Example prompts
- "Analyze the stride pattern from this week's running sessions and identify any inconsistencies."
- "Compare the gait data between two users to determine which has a more efficient walking pattern."
- "Detect potential injury risks based on the latest stride analysis report."
Tips & gotchas
Ensure that input data is properly formatted and calibrated for accurate results. The skill may require additional sensor or motion capture integration for detailed biomechanical insights.
Tags
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