refactor
This Claude Code skill performs intelligent code refactoring with full codebase awareness across specified scopes using safe or aggressive strategies. Use it when you need to refactor specific files, symbols, or patterns while maintaining test coverage and preventing regression, requiring clear intent about the target and desired outcome before execution begins.
git clone --depth 1 https://github.com/code-yeongyu/oh-my-openagent /tmp/refactor && cp -r /tmp/refactor/packages/shared-skills/skills/refactor ~/.claude/skills/refactorSKILL.md
export const REFACTOR_TEMPLATE = `# Intelligent Refactor Command
## Usage
\`\`\`
/refactor <refactoring-target> [--scope=<file|module|project>] [--strategy=<safe|aggressive>]
Arguments:
refactoring-target: What to refactor. Can be:
- File path: src/auth/handler.ts
- Symbol name: "AuthService class"
- Pattern: "all functions using deprecated API"
- Description: "extract validation logic into separate module"
Options:
--scope: Refactoring scope (default: module)
- file: Single file only
- module: Module/directory scope
- project: Entire codebase
--strategy: Risk tolerance (default: safe)
- safe: Conservative, maximum test coverage required
- aggressive: Allow broader changes with adequate coverage
\`\`\`
## What This Command Does
Performs intelligent, deterministic refactoring with full codebase awareness. Unlike blind search-and-replace, this command:
1. **Understands your intent** - Analyzes what you actually want to achieve
2. **Maps the codebase** - Builds a definitive codemap before touching anything
3. **Assesses risk** - Evaluates test coverage and determines verification strategy
4. **Plans meticulously** - Creates a detailed plan with Plan agent
5. **Executes precisely** - Step-by-step refactoring with LSP and AST-grep
6. **Verifies constantly** - Runs tests after each change to ensure zero regression
---
# PHASE 0: INTENT GATE (MANDATORY FIRST STEP)
**BEFORE ANY ACTION, classify and validate the request.**
## Step 0.1: Parse Request Type
| Signal | Classification | Action |
|--------|----------------|--------|
| Specific file/symbol | Explicit | Proceed to codebase analysis |
| "Refactor X to Y" | Clear transformation | Proceed to codebase analysis |
| "Improve", "Clean up" | Open-ended | **MUST ask**: "What specific improvement?" |
| Ambiguous scope | Uncertain | **MUST ask**: "Which modules/files?" |
| Missing context | Incomplete | **MUST ask**: "What's the desired outcome?" |
## Step 0.2: Validate Understanding
Before proceeding, confirm:
- [ ] Target is clearly identified
- [ ] Desired outcome is understood
- [ ] Scope is defined (file/module/project)
- [ ] Success criteria can be articulated
**If ANY of above is unclear, ASK CLARIFYING QUESTION:**
\`\`\`
I want to make sure I understand the refactoring goal correctly.
**What I understood**: [interpretation]
**What I'm unsure about**: [specific ambiguity]
Options I see:
1. [Option A] - [implications]
2. [Option B] - [implications]
**My recommendation**: [suggestion with reasoning]
Should I proceed with [recommendation], or would you prefer differently?
\`\`\`
## Step 0.3: Create Initial Todos
**IMMEDIATELY after understanding the request, create todos:**
\`\`\`
TodoWrite([
{"id": "phase-1", "content": "PHASE 1: Codebase Analysis - launch parallel explore agents", "status": "pending", "priority": "high"},
{"id": "phase-2", "content": "PHASE 2: Build Codemap - map dependencies and impact zones", "status": "pending", "priority": "high"},
{"id": "phase-3", "content": "PHASE 3: Test Assessment - analyze test coverage and verification strategy", "status": "pending", "priority": "high"},
{"id": "phase-4", "content": "PHASE 4: Plan Generation - invoke Plan agent for detailed refactoring plan", "status": "pending", "priority": "high"},
{"id": "phase-5", "content": "PHASE 5: Execute Refactoring - step-by-step with continuous verification", "status": "pending", "priority": "high"},
{"id": "phase-6", "content": "PHASE 6: Final Verification - full test suite and regression check", "status": "pending", "priority": "high"}
])
\`\`\`
---
# PHASE 1: CODEBASE ANALYSIS (PARALLEL EXPLORATION)
**Mark phase-1 as in_progress.**
## 1.1: Launch Parallel Explore Agents (BACKGROUND)
Fire ALL of these simultaneously using \`call_omo_agent\`:
\`\`\`
// Agent 1: Find the refactoring target
call_omo_agent(
subagent_type="explore",
run_in_background=true,
prompt="Find all occurrences and definitions of [TARGET].
Report: file paths, line numbers, usage patterns."
)
// Agent 2: Find related code
call_omo_agent(
subagent_type="explore",
run_in_background=true,
prompt="Find all code that imports, uses, or depends on [TARGET].
Report: dependency chains, import graphs."
)
// Agent 3: Find similar patterns
call_omo_agent(
subagent_type="explore",
run_in_background=true,
prompt="Find similar code patterns to [TARGET] in the codebase.
Report: analogous implementations, established conventions."
)
// Agent 4: Find tests
call_omo_agent(
subagent_type="explore",
run_in_background=true,
prompt="Find all test files related to [TARGET].
Report: test file paths, test case names, coverage indicators."
)
// Agent 5: Architecture context
call_omo_agent(
subagent_type="explore",
run_in_background=true,
prompt="Find architectural patterns and module organization around [TARGET].
Report: module boundaries, layer structure, design patterns in use."
)
\`\`\`
## 1.2: Direct Tool Exploration (WHILE AGENTS RUN)
While background agents are running, use direct tools:
### LSP Tools for Precise Analysis:
\`\`\`typescript
// Find definition(s)
LspGotoDefinition(filePath, line, character) // Where is it defined?
// Find ALL usages across workspace
LspFindReferences(filePath, line, character, includeDeclaration=true)
// Get file structure
LspDocumentSymbols(filePath) // Hierarchical outline
LspWorkspaceSymbols(filePath, query="[target_symbol]") // Search by name
// Get current diagnostics
lsp_diagnostics(filePath) // Errors, warnings before we start
\`\`\`
### AST-Grep Skill for Pattern Analysis:
\`\`\`bash
// Find structural patterns
python3 scripts/ast_grep_helper.py search 'function $NAME($$$) { $$$ }' --lang ts src/
# Preview refactoring first
sg --pattern '[old_pattern]' --rewrite '[new_pattern]' --lang ts src/
\`\`\`
### Grep for Text Patterns:
\`\`\`
grep(pattern="[search_term]", path="src/", include="*.ts")
\`\`\`
## 1.3: Collect BackgrounAutomates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Use ast-grep (sg) for AST-aware code search and rewrite across 25 languages. Trigger for structural code matching or deterministic codemods: find every function/call/class/import shaped like X, rewrite console.log to logger.info, strip `as any`, migrate require() to import, find empty catch blocks or missing await, and scan/apply YAML rules. Prefer this over rg/grep when the target is syntax shape rather than text; use rg for string contents, comments, filenames, or regex-style byte searches.
QA the omo Codex Light edition (lazycodex / packages/omo-codex) itself, in strict isolation so ONLY our plugin is exercised, never the user's real ~/.codex. The first-party method drives the real `codex app-server` against an isolated CODEX_HOME plus a LOCAL mock model (no real API call), and proves a plugin hook fired by asserting hook/started + hook/completed notifications. Also: isolated install verification, per-component hook probes, a tmux TUI smoke, and runtime log observation (RUST_LOG / logs SQLite / /debug-config). Ships tested helper scripts each with a --self-test. Use whenever someone changes anything under packages/omo-codex or wants to QA, smoke-test, verify, or debug the Codex plugin, its hooks/components, the installer/config.toml, the app-server flow, or the Codex TUI. Triggers: codex qa, qa codex, codex-qa, test codex plugin, verify codex hook, codex app-server, lazycodex qa, isolated CODEX_HOME, prove codex hook fired, codex tui test.
MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, OMO/Senpi/pi, oh-my-pi (omp), gajae-code (gjc), OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, Aside browser-agent sessions, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subagent linkage, cwd/model/time/token filters, archives, and cost clues. Expands fuzzy recall into parallel query lanes and first probes known stores so absent platforms are skipped cheaply. Triggers: coding agent sessions, Codex/Claude/OpenCode/OMO/Senpi/pi/oh-my-pi/omp/gajae-code/gjc/OpenClaw/Droid/Amp/Kodu/Cursor/Aider/Aside sessions, transcript search, session history, session ID, read transcript, token usage, subagent sessions, what did I do yesterday, did we already do this.
Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook.
Store a dag definition once and re-run it in one or two lines, instead of pasting the full definition JSON into every eval cell. MUST USE whenever the user wants to save a DAG for reuse, run a previously saved/named DAG, schedule the same graph repeatedly (nightly/weekly audits, recurring multi-agent pipelines), or asks where to put a dag definition file. Triggers: dag library, save this dag, reuse a dag, run the saved dag, stored dag definition, recurring dag, nightly dag, dag 정의 저장, 저장된 dag 실행, dag 반복 실행, DAG 만들어두고 여러 번.
Expert data processing with a hybrid engine strategy: resident-kernel engines first - DuckDB plus a resident Python stack (Polars/numpy/matplotlib) in persistent js/py eval kernels where the harness has them, bun/uv one-shots elsewhere - and per-action placement judgment (in-memory vs streaming vs remote-in-place). Triggers: 'analyze the data', 'what is in this CSV/parquet/json', 'summarize this', 'group by', 'filter rows', 'sort by', 'join these files', 'merge datasets', 'time series trend', 'compare yesterday and today', 'distribution/histogram', 'correlation', 'clean duplicates', 'handle missing values', 'dataset larger than RAM', 'SQL query on files', 'DataFrame operations', 'chart/plot this data', DuckDB vs Polars selection, quick data exploration CLI. NOT for plain text/code inspection, configs, or tiny inline math.
MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'playwright', 'flaky test', 'fails intermittently', 'passes in isolation', 'only fails in CI'.