logic-master

Codex Logic Skill

Execute logic optimization and image-based code tasks using Codex CLI in --yolo mode.

When to Use

• Logic optimization: algorithm improvements, performance tuning
• Image-based tasks: generate code from screenshots, mockups, diagrams
• Refactoring: extract functions, simplify conditionals, reduce complexity
• Business logic: validation rules, data transformations, state machines
• Debugging: fix complex logic bugs, race conditions

When NOT to Use

• Visual/styling changes (use frontend-master skill instead)
• CSS, layout, colors, typography, animations

Execution Pattern

Basic Command Structure

# Direct prompt
codex exec --yolo "<instruction>"

# With file context via stdin
cat <file> | codex exec --yolo -

# With image attachment
codex exec --yolo --image <path-to-image> "<instruction>"

# With directory context
codex exec --yolo -C <directory> "<instruction>"

Required Flags

Flag	Purpose
--yolo	MANDATORY - Auto-approve and bypass sandbox
--image or -i	Attach image files for visual context
--json	Get JSONL event stream for parsing
-o or --output-last-message	Save final output to file
-C or --cd	Change working directory
--sandbox	Set access level (workspace-write recommended)
-c, --config	Override config value; for this skill, only model_reasoning_effort should be adjusted (예: -c model_reasoning_effort="xhigh")

Model Routing (Performance-oriented)

• **이미지 기반 작업(--image 사용)**은 반드시 gpt-5.3-codex 사용.
• 이미지 미사용 작업은 가벼운 요청에서는 gpt-5.3-codex-spark 사용.
• 복잡/대규모/고난도 작업은 gpt-5.3-codex 사용.
• 모델 자체는 전환하지 않고, 조절은 model_reasoning_effort만 수행.

실무 예시:

codex exec --yolo --image screenshot.png -c model_reasoning_effort=\"xhigh\" "Analyze image context"
codex exec --yolo -c model_reasoning_effort=\"low\" "Refactor a small utility function"
codex exec --yolo -c model_reasoning_effort=\"xhigh\" "Redesign a complex scheduling algorithm"

Workflow

1. Identify task type: logic optimization or image-based
2. Prepare inputs: file content or image path
3. Construct Codex command with --yolo flag
4. Execute via bash tool
5. Capture output and delegate to subagent for implementation
6. Verify results with lsp_diagnostics

Image-Based Tasks

Generate Code from Screenshot

# UI mockup to component
codex exec --yolo --image mockup.png "Generate React component matching this design"

# Diagram to code
codex exec --yolo --image architecture.png "Implement the data flow shown in this diagram"

# Error screenshot to fix
codex exec --yolo --image error-screenshot.png "Analyze this error and provide fix"

Multiple Images

codex exec --yolo --image before.png --image after.png "Generate code to transform UI from before to after state"

Logic Optimization Tasks

Algorithm Optimization

# Optimize function
cat src/utils/sort.ts | codex exec --yolo - "Optimize this sorting algorithm for large datasets"

# Reduce complexity
cat src/services/parser.ts | codex exec --yolo - "Refactor to reduce cyclomatic complexity"

Refactoring

# Extract functions
cat src/handlers/user.ts | codex exec --yolo - "Extract reusable validation logic into separate functions"

# Simplify conditionals
cat src/logic/pricing.ts | codex exec --yolo - "Simplify nested conditionals using early returns"

Performance Tuning

# Memory optimization
cat src/data/processor.ts | codex exec --yolo - "Optimize memory usage, avoid unnecessary allocations"

# Async optimization
codex exec --yolo -C src/services "Identify and fix N+1 query patterns"

Output Handling

JSON Output for Parsing

codex exec --yolo --json "Generate utility function" | jq -r '.content'

Save to File

codex exec --yolo -o result.ts "Generate TypeScript interface from this JSON schema"

Resume Session

# Continue previous work
codex exec resume --last "Apply the suggested changes"

Integration with Subagents

After Codex CLI provides analysis/suggestions, delegate implementation:

1. TASK: Implement logic changes based on Codex analysis
2. EXPECTED OUTCOME: Optimized code matching Codex recommendations
3. REQUIRED SKILLS: logic-master
4. REQUIRED TOOLS: Bash (for codex CLI), Read, Edit, lsp_diagnostics
5. MUST DO:
   - Execute codex exec with --yolo flag first
   - Parse Codex output for implementation steps
   - Apply changes using Edit tool
   - Verify with lsp_diagnostics
   - Run tests if available
6. MUST NOT DO:
   - Modify styling/visual elements
   - Skip verification step
   - Ignore Codex warnings or caveats
7. CONTEXT: [file paths, performance requirements, constraints]

Image-Based Workflow Example

1. TASK: Generate component from design mockup
2. EXPECTED OUTCOME: Working React component matching mockup
3. REQUIRED SKILLS: logic-master
4. REQUIRED TOOLS: Bash (for codex CLI), Write, lsp_diagnostics
5. MUST DO:
   - Use codex exec --yolo --image <path> to analyze mockup
   - Create component based on Codex output
   - Match existing component patterns in codebase
   - Verify types with lsp_diagnostics
6. MUST NOT DO:
   - Generate inline styles (use existing CSS framework)
   - Create new dependencies without approval
7. CONTEXT: [mockup path, component location, existing patterns]

Example Complete Workflow

# Step 1: Analyze image and get code suggestion
codex exec --yolo --image ui-mockup.png "Analyze this mockup and describe the React component structure needed" -o analysis.md

# Step 2: Generate implementation
codex exec --yolo --image ui-mockup.png "Generate React component code for this mockup using Tailwind CSS" -o Component.tsx

# Step 3: Verify and integrate
# (delegate to subagent to place file, add imports, run diagnostics)

Troubleshooting

Issue	Solution
Image not recognized	Use absolute path or ensure file exists
Command hangs	Ensure --yolo flag is present
Sandbox errors	Add --sandbox workspace-write
Large output truncated	Use -o <file> to save full output
모델 품질/속도 조절	과도한 결과 변동이 있으면 model_reasoning_effort (low, medium, high, xhigh) 값만 조정

Security Note

--yolo mode bypasses approval and sandbox restrictions. Use only when:

• Working in version-controlled directories
• Changes can be easily reverted
• No sensitive operations or credentials involved
• Running in isolated development environment