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debugging-and-error-recovery

debugging-and-error-recovery is a skill for Claude Code, Codex from vignesh2027/AI-AGENT-SKILLS. It costs 20 tokens per session (514 once invoked), scanned A, original, MIT.

A step-by-step method for finding the root cause of software errors. It uses repeatable reproduction, evidence, a specific explanation to test, and a minimal example of the problem.

In plain words
What is it for?
Use it when tests fail, production behaves differently from development, or a bug has resisted investigation. It helps examine logs and stack traces, reduce the problem, and verify the fix.
Why use it?
It replaces random code changes with investigations that can show whether an explanation is correct or wrong.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 2repo 2mo ago A scan 20 tokens original MIT

Good fit Use it when tests fail, production behaves differently from development, or a bug has resisted investigation. It helps examine logs and stack traces, reduce the problem, and verify the fix.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vignesh2027/ai-agent-skills/debugging-and-error-recovery
View source ↗ vignesh2027/AI-AGENT-SKILLS
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add vignesh2027/AI-AGENT-SKILLS --skill debugging-and-error-recovery
Clone the repo
git clone --depth 1 https://github.com/vignesh2027/AI-AGENT-SKILLS

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for debugging-and-error-recovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/debugging-and-error-recovery/github.svg)](https://agentmods.dev/skills/vignesh2027/ai-agent-skills/debugging-and-error-recovery)
Your own site
<a href="https://agentmods.dev/skills/vignesh2027/ai-agent-skills/debugging-and-error-recovery"><img src="https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/debugging-and-error-recovery/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for debugging-and-error-recovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/vignesh2027/ai-agent-skills/debugging-and-error-recovery"><img src="https://agentmods.dev/badge/skills/vignesh2027/ai-agent-skills/debugging-and-error-recovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 514 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00020 $0.00514
Opus 5.5 $0.00008 $0.00206
Sonnet 5.5 $0.00004 $0.00103
Haiku 4.5 $0.00002 $0.00051

Measured 2mo ago against content hash c04d21ae0e34, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

debugging-and-error-recovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/debugging-and-error-recovery/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Debugging is a skill, not luck. Effective debugging is systematic: form a hypothesis, design a minimal test, validate or falsify, repeat. Random changes are not debugging — they are gambling.

When to Use

  • When a test is failing and the cause is unclear
  • When behavior in production differs from behavior in development
  • When you've been debugging the same issue for more than 30 minutes

Process

Step 1: Reproduce reliably

Before investigating: reproduce the issue consistently. If you can't reproduce it, you can't verify you've fixed it.

Step 2: Gather evidence

Read the full error message (not just the last line). Check: logs, stack traces, metrics, recent changes. What changed recently?

Step 3: Form a hypothesis

Write down a specific, falsifiable hypothesis: "I believe the error is caused by X because of Y."

Step 4: Isolate the smallest reproduction

Create the simplest possible test case that reproduces the issue. Remove everything that is not necessary for the bug to manifest.

Step 5: Test the hypothesis

Design an experiment that will either confirm or falsify your hypothesis. This often means: add a log statement, write a unit test, or add an assertion.

Step 6: Falsify or confirm

If the evidence falsifies your hypothesis: form a new hypothesis. If it confirms: find the root cause (not just the symptom).

Step 7: Fix and verify

Fix the root cause, not the symptom. Verify the fix: the minimal reproduction must no longer reproduce. The full test suite must pass.

Step 8: Write a regression test

Write a test that would have caught this bug. Add it to the test suite.

Anti-Rationalizations

"I'll try changing this and see if it works" This is not debugging. Form a hypothesis first.

"The bug is intermittent — I can't reproduce it" Intermittent bugs have causes. Add logging and wait for the next occurrence. Or: analyze the conditions under which it occurred and stress test those conditions.

Verification Requirements

Read the full file on GitHub · 58 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 58 lines · 20 tokens per session scan A c04d21ae0e34

Subscribe to this mod's changes

debugging-and-error-recovery is a skill published in the GitHub repository vignesh2027/AI-AGENT-SKILLS (2 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 514 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Claude CodeDebuggingagent-skillsai-agentscoding-agentcursor-aideveloper-tools
Related

debugging-and-error-recovery compared with skills from other repositories

debugging-and-error-recovery next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
debugging-and-error-recoveryvignesh2027/AI-AGENT-SKILLSSkill22mo agoMITA20Claude Code, Codex
stuckQwenLM/qwen-codeSkill29ktodayApache-2.0A57Claude Code
structured-debuggingQwenLM/qwen-codeSkill29ktodayApache-2.0A85Claude Code, Codex
test-failure-explorerQwenLM/qwen-codeSkill29ktodayApache-2.0A32Claude Code, Codex
rust-checkHmbown/CodeWhaleSkill41k6d agoMITA15Claude Code, Codex
debugHmbown/CodeWhaleSkill41k6d agoMITA30Claude Code, Codex
feedbackHmbown/CodewhaleSkill41k1mo agoMITA0Claude Code, Codex