Command
boundary-bbcr-fallback
Execute automatic BBCR (Collapse-Rebirth Correction) when knowledge boundaries are exceeded or reasoning fails.
@qdhenryView CommandDevelopment
Command
/remove-dead-code
Safely scan, remove, and validate dead code with multi-agent analysis and automatic backup branches
Install
$ npx -y skills add qdhenry/Claude-Command-Suite --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/remove-dead-code
Context preview
What this command does when you run it.
Safely scan, remove, and validate dead code with multi-agent analysis and automatic backup branches
Command definition
remove-dead-code.mddescription: Safely scan, remove, and validate dead code with multi-agent analysis and automatic backup branches argument-hint: [scan|remove|validate] allowed-tools: Skill(remove-dead-code)
Invoke the remove-dead-code skill for: $ARGUMENTS
Ships withclaude-command-suite
A comprehensive development toolkit designed following Anthropic's Claude Code Best Practices for AI-assisted software development.
Get the whole plugin
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6mo ago
Last commit
1y ago
Created
Repo: qdhenry/Claude-Command-Suite
Other commands on claude-command-suite.
@qdhenryView CommandCommand
boundary-detect
Analyze semantic position relative to knowledge boundaries to prevent hallucination and identify uncertainty zones.
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boundary-heatmap
Generate a visual heatmap of knowledge boundaries showing safe zones, risk areas, and semantic coverage.
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boundary-risk-assess
Evaluate the current risk level and provide detailed analysis of potential hallucination or reasoning failure.
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boundary-safe-bridge
Find and construct semantic bridges to safely navigate from current position to target concept without crossing dangerous boundaries.
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optimize-prompt
Takes an input prompt and returns ONLY a token-optimized version that preserves meaning while minimizing token count. Based on LLM tokenization principles:…
@qdhenryView Command