Skill Post-Edit Quality Audit

Problem Description

A developer has just applied a set of changes to a log-analyzer skill file and wants to make sure nothing was broken in the process. Before they commit the updated skill, they want a thorough quality audit that checks for common mistakes that can sneak in during editing: broken code syntax, invalid commands, dead links, and content that shouldn't be in the skill at all.

Audit the updated SKILL.md below and produce a structured quality report. Check every potential issue category and give a clear pass/fail result for each, with specific details where problems are found.

Output Specification

Produce a file accuracy_check.md containing:

• A structured checklist with pass/fail status for each category of check
• Specific details for any failures (what's wrong, where, suggested fix)
• A final summary indicating whether the skill is ready to publish

Input Files

The following files are provided as inputs. Extract them before beginning.

=============== FILE: skills/log-analyzer/SKILL.md ===============

name: log-analyzer description: | Analyzes application logs to identify error patterns and performance issues. Helps engineers debug production incidents and understand system behavior.

Log Analyzer

Parse and analyze application logs using our internal logq tool.

Common Queries

Find errors in the last hour:

logq query --source app-logs --level error --since 1h --format json

Count error types:

import subprocess
import json

def count_errors(log_source: str, window: str = "1h") -> dict:
    result = subprocess.run(
        ["logq", "query", "--source", log_source, "--level", "error", "--since", window, "--format", "json"],
        capture_output=True, text=True
    )
    logs = json.loads(result.stdout
    error_counts = {}
    for entry in logs:
        err_type = entry.get("error_type", "unknown")
        error_counts[err_type] = error_counts.get(err_type, 0) + 1
    return error_counts

Export results to CSV:

const { exec } = require('child_process');
const fs = require('fs');

function exportLogs(source, outputFile) {
  exec(`logq export --source ${source} --format csv --output ${outputFile}`, (err, stdout, stderr) => {
    if (err) throw err;
    console.log('Export complete:', outputFile);
  });
}

For more query patterns and aggregation options see QUERY_PATTERNS.md.

Performance Analysis

Use logq stats to get percentile breakdowns:

logq stats --source app-logs --metric response_time --percentiles 50,95,99 --since 24h

Note: HTTP is a stateless request/response protocol. Each log entry represents one request-response cycle. TCP connections may be reused. =============== END FILE ===============

=============== FILE: skills/log-analyzer/QUERY_PATTERNS.md ===============

Query Patterns Reference

Advanced logq query patterns and aggregations.

Aggregations

• logq aggregate --group-by error_type --count
• logq aggregate --group-by service --sum response_time

Time Windows

• --since 1h — last 1 hour
• --since 24h — last 24 hours
• --since 7d — last 7 days =============== END FILE ===============