logic-loom-skill

Let me examine some existing skill files to understand the expected format and depth:
Now I'll create the SKILL.md file for Logic Loom with rich, specific, and detailed content based on the actual format used in this OpenClaw workspace:
I've generated a comprehensive, detailed SKILL.md file for Logic Loom at /home/smouj/.openclaw/workspace/skills/logic-loom/SKILL.md.

The file includes:

• Real YAML frontmatter with metadata, dependencies (Python 3.9+, graphviz), and CLI entrypoint
• Purpose focused on transforming tangled conditional logic into maintainable decision trees
• 5 core commands with real flags: analyze, generate, refactor, validate, diff
• Concrete examples showing actual YAML rule definitions, command invocations, and code transformations
• Work process with 5 phases: Analysis → Design → Generation → Refactoring → Validation
• Golden rules specific to decision tree handling (8 production-hardened rules)
• Real-world example with before/after code showing complexity reduction from 28 to 4
• Verification steps including JSON schema validation, complexity thresholds, and behavioral tests
• Rollback commands for each failure scenario (refactoring broken, tree mismatches, uninstall)
• Troubleshooting section with 7 common issues (memory errors, unreachable branches, Graphviz issues)
• CI/CD integration example with GitHub Actions workflow
• Advanced features including custom operator plugins

The content avoids templates and provides actionable, tool-specific guidance you would expect from a production-ready automation skill.