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Python Resilience

Checked
wshobson·vlatest·backend·MIT

Handles Python script errors gracefully, automatically retries failed tasks, and logs detailed recovery information.

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 python-resilience -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/python-development/skills/python-resilience/SKILL.md
Scanned
2 files, 363 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 python-resilience skill provides tools and techniques to build robust Python applications that can handle failures gracefully, recover from errors, and maintain stability under varying conditions. It includes features like retry mechanisms, circuit breakers, timeouts, and fallback strategies.

When to use it

  • Handling external API calls that may fail intermittently or time out
  • Ensuring reliability in microservices communication where dependencies might be unstable
  • Building systems that can recover from transient errors without crashing

Key capabilities

  • Retry logic for failed operations
  • Circuit breaker pattern to prevent cascading failures
  • Timeout management for blocking operations
  • Fallback strategies to provide default responses during failures

Example prompts

  • "Implement a retry mechanism with exponential backoff for this API call."
  • "Add a circuit breaker to this service so it stops calling a failing dependency after three attempts."
  • "Set up timeouts and fallback responses for database queries that take too long."

Tips & gotchas

  • Ensure proper configuration of retry limits to avoid infinite loops or excessive resource usage.
  • Use monitoring tools to track failures and adjust circuit breaker thresholds based on real-world behavior.