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Error Diagnostics Error Trace

Listed
sickn33·vlatest·testing·MIT

This skill automatically traces and diagnoses errors in code, quickly pinpointing issues and saving developers valuable debugging time.

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 sickn33/agentic-awesome-skills --skill error-diagnostics-error-trace -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

sickn33

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 sickn33/antigravity-awesome-skills at 5a4cdd9df8.

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

Commit
5a4cdd9df8
Manifest
skills/error-diagnostics-error-trace/SKILL.md
Scanned
0 files
Copies in repo
3 — all of them scanned
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 error-diagnostics-error-trace skill enables AI agents to systematically analyze and interpret error logs, stack traces, and diagnostic data to pinpoint the root cause of software failures. It transforms raw, often cryptic technical output into actionable insights that guide developers toward effective solutions.

When to use it

  • Debugging complex runtime exceptions in production environments where standard logging is insufficient.
  • Analyzing crash dumps or stack traces from third-party libraries to understand dependency conflicts.
  • Automating the initial triage of CI/CD pipeline failures caused by build errors or test suite crashes.
  • Deciphering verbose server logs containing multiple interleaved error messages during deployment rollouts.

Key capabilities

  • Parses and normalizes various log formats into structured data for easier analysis.
  • Identifies causal chains between preceding events and the final system failure.
  • Highlights specific lines of code or configuration settings responsible for the anomaly.
  • Suggests potential remediation steps based on the identified error pattern.

Example prompts

  • "Analyze this stack trace from our payment service and explain why the transaction is failing."
  • "Review these server logs to find the root cause of the 503 Service Unavailable errors occurring at 14:02 UTC."
  • "Interpret this error message regarding a database connection timeout and suggest immediate fixes."

Tips & gotchas

Ensure the AI agent has access to the full context surrounding the error, including preceding log entries, as isolated traces often lack necessary causal information. This skill is most effective when combined with other diagnostic tools that provide real-time system metrics or code execution environments.