debugging-patterns
The debugging-patterns skill provides structured root cause analysis frameworks including log-first investigation methodology, git bisect correlation analysis, and pattern-based diagnosis with confidence scoring. Use this skill during the DEBUG workflow investigation phase, when build tests fail unexpectedly, or when reviewing error handling gaps to systematically gather evidence before forming hypotheses.
git clone --depth 1 https://github.com/a5c-ai/babysitter /tmp/debugging-patterns && cp -r /tmp/debugging-patterns/library/methodologies/cc10x/skills/debugging-patterns ~/.claude/skills/debugging-patternsSKILL.md
# Debugging Patterns ## Overview Provides structured frameworks for root cause analysis. The log-first methodology ensures evidence is gathered before hypotheses are formed. ## Log-First Investigation 1. Read ALL available logs, error output, and stack traces 2. DO NOT form hypotheses before reading evidence 3. Identify the exact error: message, file, line, call stack 4. Determine reproduction steps from evidence 5. Check git log for recent changes correlating with bug introduction ## Pattern-Based Diagnosis - Check patterns.md for known gotchas matching the error - Cross-reference with common patterns: null pointer, race condition, resource leak, config error - Rate root cause confidence (>=80% to proceed with fix) ## Evidence Collection - Stack traces with full call chain - Error messages with context - Exit codes from reproduction attempts - Git blame/log for change correlation - Environment differences (if applicable) ## When to Use - During DEBUG workflow investigation phase - When BUILD tests fail unexpectedly - When reviewing error handling gaps ## Agents Used - `bug-investigator` (primary consumer) - `silent-failure-hunter` (pattern reference)
Review TypeScript code changes for consistency, type safety, and monorepo patterns across babysitter packages
Generate and validate documentation for @a5c-ai/babysitter-sdk CLI commands and exported APIs
Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
Architect code review with DRY, YAGNI, abstraction, and test coverage principle enforcement