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Systematic Debugging

Checked
anorbert-cmyk·vlatest·testing

Systematically debugs CMYK color workflows, identifying and resolving issues for accurate print reproduction using AI analysis.

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 anorbert-cmyk/agentic-kit --skill systematic-debugging -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

anorbert-cmyk

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 anorbert-cmyk/agentic-kit at 3cf21ec9a5.

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

Commit
3cf21ec9a5
Manifest
.agent/skills/systematic-debugging/SKILL.md
Scanned
1 file, 98 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

This skill, systematic-debugging, provides a structured approach to identifying and resolving issues within AI agent workflows. It facilitates methodical error analysis through logging, breakpoint insertion, and variable inspection. The goal is to improve debugging efficiency by providing a clear process for isolating and fixing problems.

When to use it

  • When an AI agent consistently fails to achieve its intended outcome.
  • During the development phase of complex agents with multiple steps or dependencies.
  • To diagnose unexpected behavior in production environments where agent performance is critical.
  • When debugging a chain of tools, allowing for targeted investigation of each tool's output and impact.

Key capabilities

  • Logging: Records key variables and events during execution.
  • Breakpoint Insertion: Allows pausing execution at specific points to inspect the state.
  • Variable Inspection: Provides visibility into variable values during debugging.

Example prompts

  • "Debug this agent workflow, focusing on the data processing step."
  • "Insert a breakpoint before calling the 'summarize_document' tool and log its input."
  • "Systematically debug why my agent is failing to extract information from this webpage."

Tips & gotchas

This skill requires a foundational understanding of the AI agent’s code or workflow. Effective debugging relies on clear logging statements and strategically placed breakpoints for maximum insight.