lvlup-sw/axiom · Archived

distill

Strip backend code to its essence by identifying dead code, vestigial patterns, and unnecessary complexity.

First seen Apr 7, 2026

Installation

$ npx skills add lvlup-sw/axiom --skill distill

Summary

  • Strip backend code to its essence by identifying dead code, vestigial patterns, and unnecessary complexity.
  • Use when cleaning up after refactoring or reducing cognitive load.
  • Triggers: 'simplify code', 'find dead code', 'clean up', or /axiom:distill.
  • Do NOT use for error handling — use axiom:harden instead.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 1
License LICENSE
Default branch main
Open issues 1
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Version0.1.0
More metadata
author
lvlup-sw
version
0.1.0
category
assessment
dimensions
["hygiene","topology"]

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,890 B
  • docs SUMMARY.md 325 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Distill Skill

Overview

Simplification skill for the axiom backend quality plugin. Covers DIM-5 (Hygiene) and DIM-1 (Topology) dimensions to strip code down to its essential form by identifying dead code, vestigial patterns, and unnecessary complexity.

Triggers

Activate this skill when:

  • User says "simplify code", "find dead code", "clean up"
  • User runs /axiom:distill
  • Post-refactoring cleanup is needed
  • Reducing cognitive load in a module

Do NOT activate when:

  • Error handling improvements are needed — use axiom:harden instead
  • Performance optimization is the goal — performance profiling is out of scope for axiom
  • Security hardening is required — use axiom:harden instead

Process

1. Load Dimensions

Load the relevant quality dimensions from @skills/backend-quality/references/dimensions.md:

  • DIM-5 (Hygiene): Dead code, commented-out code, unused imports/exports, vestigial patterns
  • DIM-1 (Topology): Module structure, dependency direction, wiring complexity

2. Run Deterministic Checks

Run axiom:scan for deterministic checks on Hygiene and Topology dimensions. This produces machine-verifiable findings for:

  • Unused exports and imports
  • Unreachable code paths
  • Circular dependencies
  • Excessive module fan-out

3. Layer Qualitative Assessment

Beyond deterministic checks, apply human-judgment analysis:

Dead Code Identification

Identify unreachable branches (code after return/throw), unused exports (exported but never imported elsewhere), commented-out code (version control exists for history), and feature-flagged-off code that shipped long ago.

See @skills/distill/references/dead-code-patterns.md for detection heuristics and false positive guidance.

Vestigial Pattern Detection

Find evolutionary leftovers from previous designs. Look for divergent implementations that suggest a pattern was partially migrated, adapter layers wrapping things that no longer need adapting, and configuration for features that were removed.

Wiring Simplification

Identify manual DI that could be simpler, unnecessary indirection layers, over-abstracted factory/builder patterns where direct construction suffices, and registration ceremonies that add complexity without value.

Abstraction Audit

Flag premature abstractions, over-engineering, and single-use helpers. Ask: does this abstraction serve more than one caller? Would inlining it make the code clearer?

Code Archaeology

Identify patterns that were once necessary but no longer serve a purpose. Look for workarounds for bugs that have since been fixed, compatibility shims for deprecated APIs, and defensive code guarding against conditions that can no longer occur.

4. Output Findings

Format all findings per @skills/backend-quality/references/findings-format.md. Each finding includes:

  • Dimension (DIM-5 or DIM-1)
  • Severity (HIGH, MEDIUM, LOW)
  • Location (file, line range)
  • Description and recommended action

See also @skills/distill/references/simplification-guide.md for guidance on when to simplify vs remove.

Error Handling

  • Empty scope: If no files match the target scope, output an informative message explaining that no files were found and suggesting the user verify the path or scope parameters.
  • No findings: If analysis completes with zero findings, report a clean result rather than failing silently.