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/memtrace-quality

Find dead code, complexity hotspots, and refactoring candidates in indexed source code. Use when the user asks about source-code quality, dead code, unused functions, zero callers, complexity, cyclomatic complexity, hotspots, refactoring candidates, or code smell questions. Do

From plugin
memtrace-public
44627 skills
Install
$ npx -y skills add syncable-dev/memtrace-public --skill memtrace-quality --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/memtrace-quality

Context preview

The summary Claude sees to decide when to auto-load this skill.

Find dead code, complexity hotspots, and refactoring candidates in indexed source code. Use when the user asks about source-code quality, dead code, unused functions, zero callers, complexity, cyclomatic complexity, hotspots, refactoring candidates, or code smell questions. Do

SKILL.md

memtrace-quality.SKILL.md
name: memtrace-quality
description: "Find dead code, complexity hotspots, and refactoring candidates in indexed source code. Use when the user asks about source-code quality, dead code, unused functions, zero callers, complexity, cyclomatic complexity, hotspots, refactoring candidates, or code smell questions. Do not use Grep, Glob, rg, or manual reference search for unused code; Memtrace uses graph reachability and complexity metrics."

Overview

Code quality via graph analysis — dead code, complexity hotspots, repository stats.

Quick Reference

| Tool | Purpose | Required | Key optional | |------|---------|----------|--------------| | `find_dead_code` | Zero-caller symbols | `repo_id` | `include_tests`, `limit`, `kinds[]` | | `find_most_complex_functions` | Ranked complexity hotspots | `repo_id` | **`top_n`** (def 20) — not `limit` | | `calculate_cyclomatic_complexity` | Score one symbol | `repo_id`, **`target`** | — | | `get_repository_stats` | Repository overview | `repo_id` | `branch` |

> **Parameter types:** numbers must be JSON numbers — `limit: 20`, never `"20"` (MCP error -32602).

Full parameter spec for every Memtrace tool: `references/mcp-parameters.md` (bundled at the memtrace-skills plugin root).

Steps

1. Repository overview

{ "repo_id": "memdb" }

2. Dead code

{ "repo_id": "memdb", "include_tests": false, "limit": 50 }

Exported symbols and entry points excluded by default. Results are candidates, not proof — callers via dynamic dispatch or reflection are invisible to the graph; verify before deleting.

3. Complexity hotspots

{ "repo_id": "memdb", "top_n": 10 }

Ordered by call-graph out-degree.

| Score | Rating | Action | |-------|--------|--------| | <5 | Low | Fine | | 5-10 | Medium | Consider simplifying | | 10-20 | High | Refactor candidate | | >20 | Critical | Refactor priority |

4. Single symbol complexity

{ "repo_id": "memdb", "target": "processOrder" }

Output

| Result | Carries | |--------|---------| | Dead-code entry (`find_dead_code`) | Symbol name + kind with zero graph callers — e.g. `format_legacy` (Function) | | Complexity row (`find_most_complex_functions`) | Symbol, complexity score, risk level — e.g. `processOrder` — 27, Critical | | Single score (`calculate_cyclomatic_complexity`) | Cyclomatic complexity for `target` | | Stats (`get_repository_stats`) | Node counts by kind, edge counts, community and process counts for `repo_id`/`branch` |

Common Mistakes

| Mistake | Reality | |---------|---------| | `find_most_complex_functions(limit: 10)` | Param is **`top_n`** | | `calculate_cyclomatic_complexity(symbol_id=...)` | Required param is **`target`** | | Only looking at the highest complexity | Medium-complexity functions that are growing (check `get_evolution`) are often more urgent |

Read more
Ships withmemtrace-public

Structural memory for AI coding agents. Bi-temporal graph, MCP-native, zero LLM calls. Cursor · Claude Code · Codex · Hermes · VS Code · Windsurf.

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