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Parse application logs and find root causes. Use when the user shares logs, stack traces, or asks what is causing errors.
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Based on SOC occupation classification
Full QA audit orchestrator. Use when the user asks to "test my app", "run a full QA audit", "test everything", or invokes /qa-audit. Discovers what kind of application this is, selects the relevant QA agents (ui-inspector, api-sentinel, security-scout, perf-guardian, data-validator, regression-watcher), runs them, and merges their reports into one master QA report.
Onboard the QA toolkit onto any project. Use on first contact with a new codebase, when the user says "set up QA", "qa init", "/qa-init", or when any QA agent finds no qa-profile.md. Studies the project deeply and writes the persistent QA profile that every other agent reads first — the toolkit's long-term memory for this project.
Wire the QA suite into CI. Use when the user wants tests running automatically on every PR or on a schedule: "add this to CI", "run tests on every push", "/qa-ci". Generates GitHub Actions workflows for the generated Playwright suite and (optionally) scheduled full audits.
Self-healing for the generated test suite. Use when previously-green Playwright tests are failing, the user says "my tests broke", "fix the tests", "/qa-heal", or after a UI refactor breaks selectors. Classifies each failure (real bug vs test drift) and repairs the drift — never papers over real bugs.
Compare two QA audit runs and report what improved, what regressed, and what persists. Use when the user asks "did it improve since last time?", "compare audits", "QA trend", or invokes /qa-trend. Requires at least two timestamped runs under qa-reports/runs/.
Audit web pages for WCAG 2.1 compliance. Use when the user asks about accessibility, a11y, WCAG, screen readers, or contrast issues.
| name | log-analyzer |
| description | Parse application logs and find root causes. Use when the user shares logs, stack traces, or asks what is causing errors. |
Parse, analyze, and extract insights from application logs and error traces.
This skill analyzes application logs, error traces, and system output to identify patterns, root causes, and anomalies. It processes log files in any common format and produces actionable insights for debugging and quality analysis.
When the user provides log files, error outputs, or stack traces:
[timestamp] [level] [source] message# Log Analysis Report
**File**: [filename]
**Period**: [start] to [end]
**Total Entries**: [count]
## Summary
| Level | Count | Percentage |
|-------|-------|------------|
| ERROR | X | X% |
| WARN | X | X% |
| INFO | X | X% |
## Top Errors (by frequency)
| # | Error Pattern | Count | First Seen | Last Seen |
|---|--------------|-------|------------|-----------|
| 1 | [pattern] | X | [time] | [time] |
## Root Cause Analysis
### Issue 1: [Title]
- **Error**: [error message pattern]
- **Frequency**: X occurrences in Y period
- **Likely Cause**: [analysis]
- **Recommended Action**: [fix suggestion]
- **Related Log Entries**: [line numbers or timestamps]
## Timeline
[Chronological narrative of significant events]
## Recommendations
1. [Prioritized action items]
Analyze this application log file and tell me what's causing the 500 errors:
[paste log content]
Here's a stack trace from our production crash. What's the root cause?
[paste stack trace]