Provides Codex CLI delegation workflows for complex code generation and development tasks using OpenAI's GPT-5.3-codex models, including English prompt formulation, execution flags, sandbox modes, and safe result handling. Use when the user explicitly asks to use Codex for complex programming tasks such as code generation, refactoring, or architectural analysis. Triggers on "use codex", "delegate to codex", "run codex cli", "ask codex", "codex exec", "codex review".
Provides Codex CLI delegation workflows for complex code generation and development tasks using OpenAI's GPT-5.3-codex models, including English prompt formulation, execution flags, sandbox modes, and safe result handling. Use when the user explicitly asks to use Codex for complex programming tasks such as code generation, refactoring, or architectural analysis. Triggers on "use codex", "delegate to codex", "run codex cli", "ask codex", "codex exec", "codex review".
allowed-tools
Bash, Read, Write
Codex CLI Delegation
Delegate specific complex development tasks to OpenAI's Codex CLI when the user explicitly requests Codex, especially for tasks requiring advanced code generation capabilities.
Overview
This skill provides a safe and consistent workflow to:
convert the task request into English before execution
run codex exec or codex review in non-interactive mode for deterministic outputs
support model, sandbox, approval, and execution options
return formatted results to the user for decision-making
This skill complements existing capabilities by delegating complex programming tasks to Codex when requested, leveraging OpenAI's GPT-5.3-codex models for advanced code generation and analysis.
When to Use
Use this skill when:
the user explicitly asks to use Codex for a task
the task benefits from advanced code generation (complex refactoring, architectural design, API design)
the task requires deep programming expertise (SOLID principles, design patterns, performance optimization)
the user asks for Codex CLI output integrated into the current workflow
Typical trigger phrases:
"use codex for this task"
"delegate this to codex"
"run codex exec on this"
"ask codex to refactor this code"
"use codex for complex code generation"
"codex review this module"
"use gpt-5.3 for this task"
"use o3 for complex reasoning"
"use o4-mini for faster iteration"
Prerequisites
Verify tool availability before delegation:
codex --version
If unavailable, inform the user and stop execution until Codex CLI is installed.
ask for actionable, verifiable results with file paths
specify acceptance criteria when applicable
Example transformation:
user intent: "refactorizza questa classe per SOLID principles"
Codex prompt (English): "Refactor this class to follow SOLID principles. Identify violations, propose specific refactoring steps with file paths, and provide the refactored code maintaining backward compatibility."
Step 3: Select Execution Mode and Flags
For Code Generation/Development Tasks
Preferred baseline command:
codex exec"<english-prompt>"
Supported options:
-m, --model <model-id> for model selection (e.g., gpt-5.3-codex, o4-mini, o3)
-a, --ask-for-approval <policy> for approval policy:
untrusted: Only run trusted commands without approval
on-request: Model decides when to ask (recommended for development)
never: Never ask for approval (use with caution)
-s, --sandbox <mode> for sandbox policy:
read-only: No writes, no network (safest for analysis)
workspace-write: Allow writes in workspace, no network (default for development)
-i, --image <FILE> for multimodal input (repeatable)
--search to enable live web search
--full-auto as convenience alias for -a on-request -s workspace-write
Safety guidance:
prefer read-only sandbox for analysis-only tasks
use workspace-write sandbox for code generation/refactoring
prefer on-request approval for development tasks
use never approval only with explicit user consent for automated tasks
NEVER use danger-full-access without explicit user approval and external sandboxing
For multi-turn conversations, consider using codex resume --last to continue from previous sessions
For Code Review Tasks
Use the dedicated review command:
codex review "<english-prompt>"
The review command includes optimizations for code analysis and supports the same flags as codex exec.
Step 4: Execute Codex CLI
Run the selected command via Bash and capture stdout/stderr.
Examples:
# Default non-interactive delegation
codex exec"Refactor this authentication module to use JWT with proper error handling"# Explicit model and safe settings
codex exec"Review this codebase for security vulnerabilities. Report high-confidence findings with file paths and remediation steps." -m gpt-5.3-codex -a on-request -s read-only
# Code review with workspace write
codex review "Analyze this pull request for potential bugs, performance issues, and code quality concerns. Provide specific line references." -a on-request -s workspace-write
# Complex refactoring with working directory
codex exec -C ./src "Refactor these service classes to use dependency injection. Maintain all existing interfaces." -a on-request -s workspace-write
# With web search for latest best practices
codex exec --search "Implement OAuth2 authorization code flow using the latest security best practices and modern libraries"# Multimodal analysis
codex exec -i screenshot.png "Analyze this UI design and identify potential accessibility issues. Suggest specific improvements with code examples."# Full automation (use with caution)
codex exec --full-auto "Generate unit tests for all service methods with >80% coverage"
Step 5: Return Results Safely
When reporting Codex output:
summarize key findings, generated code, and confidence level
keep raw output available when needed for detailed review
separate observations from recommended actions
explicitly ask user confirmation before applying suggested edits
highlight any security implications or breaking changes
Output Template
Use this structure when returning delegated results:
## Codex Delegation Result### Task
[delegated task summary]
### Command`codex exec ...`### Key Findings- Finding 1
- Finding 2
### Generated Code/Changes
[summary of code generated or changes proposed]
### Suggested Next Actions1. Action 1
2. Action 2
### Notes- Output language from Codex: English
- Sandbox mode: [mode used]
- Requires user approval before applying code changes
Examples
Example 1: Complex refactoring for SOLID principles
codex exec"Refactor this OrderService class to follow SOLID principles. Current issues: 1) Single Responsibility violated (handles validation, processing, notification), 2) Open/Closed violated (hard-coded payment providers), 3) Dependency Inversion violated (concrete dependencies). Provide: 1) Proposed class structure, 2) Step-by-step migration plan, 3) Refactored code maintaining backward compatibility." -m gpt-5.3-codex -a on-request -s workspace-write
Example 2: Security vulnerability analysis
codex exec"Perform a comprehensive security analysis of this authentication module. Focus on: SQL injection, XSS, CSRF, authentication bypass, session management, and password handling. For each vulnerability found, provide: severity level, CWE identifier, exploit scenario, and concrete remediation with code examples." -a on-request -s read-only
Example 3: API design and implementation
codex exec --search "Design and implement a RESTful API for user management following REST best practices. Include: endpoint design, request/response schemas with validation, error handling, authentication middleware, pagination, filtering, and HATEOAS links. Use the latest industry standards and provide OpenAPI 3.0 specification."
Example 4: Performance optimization
codex exec"Analyze this database query module for performance bottlenecks. Identify: N+1 queries, missing indexes, inefficient joins, and caching opportunities. Provide: 1) Performance analysis with metrics, 2) Specific optimization recommendations, 3) Refactored code with query optimizations, 4) Migration script for database changes."
Example 5: Code review of pull request
codex review "Review this pull request for: 1) Correctness and logic errors, 2) Performance issues, 3) Security vulnerabilities, 4) Code quality and maintainability, 5) Test coverage gaps, 6) Documentation completeness. Provide specific line references and actionable feedback." -a on-request -s read-only
Example 6: Multimodal UI analysis
codex exec -i design-mockup.png -i current-implementation.png "Compare the design mockup with the current implementation. Identify: layout differences, missing components, styling inconsistencies, and accessibility issues. Provide: 1) Gap analysis, 2) Specific CSS/HTML changes needed, 3) Priority ranking of fixes."
Best Practices
Prompt engineering: Include specific acceptance criteria and constraints in prompts
Sandbox selection: Use read-only for analysis, workspace-write for development
Model selection: Use gpt-5.3-codex for complex tasks, o4-mini for faster iterations
Incremental delegation: Run multiple focused delegations instead of one vague prompt
Code review: Prefer codex review for review tasks over codex exec
Verification: Always review generated code before applying
Web search: Enable --search for tasks requiring latest best practices or library versions
Multimodal: Use -i for UI/UX analysis, diagram understanding, or visual debugging
Constraints and Warnings
Sandbox safety: danger-full-access mode removes ALL security restrictions and should NEVER be used without external sandboxing (e.g., containers, VMs)
Approval policies: never policy can execute destructive commands without confirmation
Output quality: Codex output may contain bugs, security vulnerabilities, or inefficient code
Context limits: Very large tasks may exceed model context; break into smaller sub-tasks
