melech-prune

Solid

Audit and remove dead code, AI residue, and unnecessary complexity after iteration.

AI & Automation 13 stars 3 forks Updated 2 days ago MIT

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Skill Content

# Prune After 5–15 prompts of iterative coding with AI, codebases accrete **AI residue**: orphaned helpers from earlier prompts, dead types, half-migrated state, speculative config keys, and zombie workflows. The feature works and tests might pass, but the working diff is cluttered with dead pathways and unreferenced scaffolding. **`melech-prune` acts as an evidentiary garbage collector and architectural reconciler.** --- ## The Core Philosophy: Inverted Burden of Proof In normal coding, developers assume: *"The AI wrote this, so it's probably needed."* **`melech-prune` flips this assumption entirely:** > **Every added or modified function, type, parameter, state hook, wrapper, and export is assumed GUILTY (dead code, accidental residue, or YAGNI bloat) until proven innocent with concrete evidence.** If a symbol cannot provide proof of reachability and concrete necessity, it is queued for deletion. --- ## The 4 Evidentiary Proofs To survive pruning, every symbol in the audited diff must satisfy these four tests: | Proof Type | Question Asked | Evidentiary Requirement | If Proof Fails | |---|---|---|---| | **1. Reachability Proof** | "Can runtime execution actually reach this?" | Trace a direct call chain from an active entrypoint (route, UI component, CLI command, export, or event handler). | **Dead / Zombie Code** → Purge. | | **2. Requirement Proof** | "Which explicit user requirement demanded this?" | Identify the exact user story or bugfix requiring this branc...

Details

Author
AdirD
Repository
AdirD/agent-shell-hamelech
Created
1 months ago
Last Updated
2 days ago
Language
Python
License
MIT

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