Structured debugging methodology using hypothesis-driven investigation, log analysis, and bisection to isolate and resolve defects.
Scanned 5/29/2026
Install to Claude Code
npx -y skills add a5c-ai/babysitter --skill systematic-debugging --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Systematic Debugging?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/a5c-ai-systematic-debugging)More formats (shields.io, HTML) on the badges page.
---
name: systematic-debugging
description: Structured debugging methodology using hypothesis-driven investigation, log analysis, and bisection to isolate and resolve defects.
allowed-tools: Read, Write, Edit, Bash, Grep, Glob, WebFetch, WebSearch, Agent, AskUserQuestion
---
# Systematic Debugging
## Overview
Structured approach to investigating and resolving defects using hypothesis-driven methodology rather than trial-and-error.
## When to Use
- Step verification fails during implementation
- Unexpected behavior discovered during testing
- Bug reports require investigation
- Performance issues need root cause analysis
## Process
1. **Reproduce** - Confirm the defect with a minimal reproduction
2. **Hypothesize** - Form theories about the root cause
3. **Investigate** - Systematically test hypotheses (logs, breakpoints, bisection)
4. **Isolate** - Narrow to the specific component/line
5. **Fix** - Apply targeted fix addressing root cause
6. **Verify** - Confirm fix resolves the issue without regression
## Key Rules
- Never apply fixes without understanding the root cause
- Use web-researcher agent for unfamiliar error patterns
- Document the investigation path for future reference
- Verify that the fix does not introduce regressions
## Tool Use
Integrated into `methodologies/rpikit/rpikit-implement` (failure handling)
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.