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Stride Analysis Patterns

Checked
wshobson·vlatest·other·MIT

Helps with analysis, patterns as part of agent workflows workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add wshobson/agents --skill stride-analysis-patterns -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

wshobson

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned wshobson/agents at 46891e7e60.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
46891e7e60
Manifest
plugins/security-scanning/skills/stride-analysis-patterns/SKILL.md
Scanned
2 files, 651 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

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.