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Self Improvement Ci

Checked
pskoett·vlatest·agents

This CI skill automatically refines its responses based on user feedback, continuously improving accuracy and relevance for a better experience.

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 pskoett/pskoett-ai-skills --skill self-improvement-ci -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

pskoett

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 pskoett/pskoett-ai-skills at 8a71d7098d.

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

Commit
8a71d7098d
Manifest
skills/self-improvement-ci/SKILL.md
Scanned
2 files, 162 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

The self-improvement-ci skill enables AI agents to autonomously analyze their own performance and generate targeted improvement strategies based on specific feedback or goals. It functions as a continuous learning loop, allowing agents to refine their reasoning, coding accuracy, or communication style without external retraining.

When to use it

  • Post-execution review: Trigger immediately after an agent completes a complex task to identify logical gaps or errors in its output.
  • Skill acquisition: Instruct the agent to learn a new framework or tool by analyzing its initial failures and generating a study plan.
  • Tone calibration: Ask the agent to adjust its communication style (e.g., more formal, more concise) based on user feedback from previous interactions.
  • Edge case handling: Request strategies for handling specific types of ambiguous inputs that previously caused the agent to hallucinate or fail.

Key capabilities

  • Self-diagnosis of past performance errors.
  • Generation of actionable improvement plans.
  • Iterative refinement of reasoning patterns.
  • Adaptation to new constraints or domain knowledge.

Example prompts

  • "Review your last three responses regarding Python data processing and create a checklist to prevent similar logic errors in future tasks."
  • "I found your explanation of quantum computing too dense. Propose a strategy to simplify your technical explanations for non-expert audiences."
  • "Analyze why you struggled with the SQL query optimization task yesterday and outline three specific steps to improve your database query generation."

Tips & gotchas

Ensure the agent has access to its own conversation history or output logs, as it cannot self-improve without data on past performance. This skill is most effective when paired with clear, constructive feedback rather than vague criticism.