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Systematic Debugging (Grade A) logo

Systematic Debugging (Grade A)Security-tested research skill for Claude AI. Grade A. Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

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Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

Systematic Debugging is a security-tested research skill for Claude AI, designed to help developers identify and fix technical issues in a methodical and reliable way. It emphasizes the importance of finding the root cause of a problem before attempting to fix it. The skill consists of four phases: Root Cause Investigation, Pattern Analysis, and two additional phases not detailed in the provided text. It is intended for use in a variety of situations, including test failures, bugs in production, unexpected behavior, performance problems, build failures, and integration issues. The approach helps prevent quick fixes that may create new bugs and ensures that fixes are based on a thorough understanding of the issue.

Key features

  • Root cause investigation
  • Reproduction of issues
  • Analysis of recent changes
  • Diagnostic instrumentation for multi-component systems
  • Pattern analysis

Pricing

Model
Free
Category
Skills
Rating
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Use cases

Debugging a Test Failure

Use Systematic Debugging to identify the root cause of a test failure, ensuring that the fix addresses the underlying issue rather than just masking the symptoms.

Resolving a Production Bug

Apply Systematic Debugging to a bug in production, following the four phases to gather evidence, analyze patterns, and implement a reliable fix.

Troubleshooting Unexpected Behavior

Utilize Systematic Debugging to investigate unexpected behavior in a system, methodically identifying the root cause and implementing a fix that resolves the issue.

Pros & Cons

Pros

  • Encourages methodical and thorough debugging
  • Helps prevent quick fixes that may create new bugs
  • Ensures fixes are based on a thorough understanding of the issue
  • Applicable to a wide range of technical issues

Cons

  • May be time-consuming to complete all phases
  • Requires careful attention to detail and patience

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Q&A

Can I use this alongside other Claude Code plugins?

Yes. SupaConductor uses the /orchestrator-supaconductor: namespace and doesn't conflict with any other plugins, built-in commands, or MCP servers.

Asked by Camille Laurent · Jun 21, 2026

Is this overkill for small tasks?

For a quick one-file fix — yes, just use Claude Code directly. Use SupaConductor when the work touches 3 or more files, you would normally plan before coding, you want automated quality checks, or you want the work done right the first time. You can also use individual commands without the full loop.

Asked by Larisa Ionescu · Jun 21, 2026

Does this work with Cursor, Windsurf, or other AI tools?

No — SupaConductor is a Claude Code plugin that requires Claude Code's plugin system (agents, skills, slash commands, hooks). However, the conductor/ directory it creates is just Markdown files. Any AI tool can read them, so you can start with SupaConductor and switch tools later while keeping your specs, plans, and documentation.

Asked by Mei-Ling Wong · Jun 9, 2026

How much of my context window does this use?

Skills use progressive disclosure — only ~100 tokens each for metadata. Full instructions load only when activated (typically under 5,000 tokens each). The 39 skills are not loaded all at once. Agents run as separate conversations with their own context windows, so they don't fill up your main conversation. Context usage: Orchestrator ~4,000 tokens (active during /go); Planner ~3,000 tokens (during planning only); Evaluator ~2,500 tokens each (only when active); Board meeting ~5,000 tokens (on-demand); Idle ~500 tokens (between steps).

Asked by Aisha Khan · May 20, 2026

How much does this cost in API credits?

SupaConductor uses the same Claude API as normal Claude Code — it just structures the work more carefully. Because it runs multiple agents (planning, execution, evaluation), it uses roughly 3-5x the API calls compared to doing everything manually in one conversation. SupaConductor optimizes costs automatically: it uses Opus (the most capable model) for planning and evaluation, and Sonnet (faster, cheaper) for execution tasks. Ways to reduce cost include using /orchestrator-supaconductor:implement if you write specs yourself, skipping board meetings for small features (they're opt-in), and using human-in-the-loop mode to stay in control of scope.

Asked by Sami Virtanen · May 11, 2026

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