# Diagnose Software Failures Systematically

Complex failures produce scattered evidence and uncertain fixes. This skill organizes triage, ranked hypotheses, root cause analysis, validation, and prevention.

## Install

```bash
npx skillstore add sickn33/debugging-toolkit-smart-debug
```

## Metadata

- Status: approved
- Slug: sickn33-debugging-toolkit-smart-debug
- Skillstore revision: r2
- Version status: missing
- Tree hash: b6b412811f6a91dadc0bc249b54628b69e454288f61da6c5bf1df9aad2129460
- Author: sickn33
- GitHub username: sickn33
- License: MIT
- Repository: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/debugging-toolkit-smart-debug
- Ref: f9e2c34b4f19c7f3e6b0a1e93227b5f77cc12526
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: external\_commands
- Quality score: 79
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/sickn33-debugging-toolkit-smart-debug
- Manifest: https://skillstore.pages.dev/api/skills/sickn33-debugging-toolkit-smart-debug/manifest

## Capabilities

- Extracts errors, reproduction steps, affected components, environments, and failure patterns from an issue description.
- Generates ranked root cause hypotheses with evidence, probability, falsification criteria, and testing approaches.
- Selects debugging strategies based on reproducibility, environment, state complexity, load sensitivity, and failure frequency.
- Plans production-safe instrumentation using traces, conditional logging, profiling, protected endpoints, and canary traffic.
- Structures fix proposals with impact, risk, tests, rollback, validation, monitoring, and prevention actions.

## Use Cases

- Triage Application Errors: Convert an error report into ranked causes, evidence needs, and the next diagnostic action.
- Investigate Production Incidents: Correlate logs, metrics, traces, and deployments while planning production-safe instrumentation and validation.
- Review Fix Readiness: Assess a proposed fix for impact, regression coverage, rollback needs, monitoring, and prevention actions.

## Prompt Templates

### Summarize an Error

```
Analyze this error: [error]. Summarize the issue, ask for missing context, and list three likely causes in probability order.
```

### Rank Debugging Hypotheses

```
Given [stack trace] and [reproduction steps], rank hypotheses, cite evidence, define falsification criteria, and recommend the next diagnostic action.
```

### Plan Production Diagnostics

```
Create a production-safe plan for [service issue] using available logs, metrics, and traces. Include instrumentation, access safeguards, validation, and rollback.
```

### Correlate Evidence and Fix

```
Correlate [deployment timeline], [traces], [metrics], and [code changes]. Identify the root cause, propose a minimal fix, and design regression tests.
```

## Limitations

- It does not access observability platforms unless the host provides suitable tools and permissions.
- Its hypotheses depend on the accuracy and completeness of supplied errors, traces, metrics, code, and reproduction details.
- Example integrations are illustrative and may require project-specific APIs, credentials, and implementation.
- Production changes still require human approval, access controls, testing, monitoring, and rollback preparation.

## Best Practices

- Provide exact errors, timestamps, environments, reproduction steps, recent deployments, and relevant logs before requesting a diagnosis.
- Test each hypothesis with explicit falsification criteria before changing production code.
- Validate fixes with regression tests, baseline comparisons, canary monitoring, and a documented rollback plan.

## Anti Patterns

- Do not accept a root cause that lacks supporting evidence from code, logs, traces, metrics, or reproduction.
- Do not enable broad production logging without access controls, sampling, retention limits, and sensitive-data review.
- Do not deploy speculative fixes without tests, monitoring thresholds, impact assessment, and rollback preparation.

## Security Audit

- Audited at: 2026-07-23T23:05:25.727\+00:00
- Summary: All three static findings are false positives caused by Markdown backticks, a TypeScript example fence, and ordinary validation text. The skill contains no executable commands or network reconnaissance instructions.

## Stats

- Views: 104
- Downloads: 10
- Favorites: 0
- Popularity score: 0