Codex CLI Delegation & Code Generation Routing
Intelligently delegate code generation, boilerplate creation, and automation tasks to OpenAI Codex CLI for rapid prototyping and development.
Best use case
Codex CLI Delegation & Code Generation Routing is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Intelligently delegate code generation, boilerplate creation, and automation tasks to OpenAI Codex CLI for rapid prototyping and development.
Teams using Codex CLI Delegation & Code Generation Routing should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/core-codex-delegator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Codex CLI Delegation & Code Generation Routing Compares
| Feature / Agent | Codex CLI Delegation & Code Generation Routing | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Intelligently delegate code generation, boilerplate creation, and automation tasks to OpenAI Codex CLI for rapid prototyping and development.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
## Purpose & When-To-Use
**Trigger this skill when:**
* User requests generation of new code from scratch (boilerplate, scaffolds, templates)
* Task involves creating test suites from existing code
* Rapid prototyping with natural language specifications is needed
* Large-scale repetitive code patterns must be generated
* Multi-file project initialization is required
* Converting pseudocode or diagrams to implementation
**Do NOT trigger when:**
* Debugging existing code with business context
* Refactoring code requiring architectural understanding
* Performing code review or security analysis
* Modifying existing code with complex dependencies
* Interactive problem-solving requiring domain expertise
## Pre-Checks
**Time normalization:**
```
NOW_ET = 2025-10-26T01:18:52-04:00
```
**Input validation:**
1. Verify `task_description` is non-empty and specific
2. Confirm `task_type` is one of: generation, modification, analysis, testing
3. Check `existing_files` list for valid paths if task_type = modification
4. Validate Codex CLI availability: `which codex` returns valid path
5. Confirm Codex authentication: check `~/.codex/config.toml` exists or user is authenticated
**Source freshness:**
* Codex CLI repo (https://github.com/openai/codex, accessed 2025-10-26T01:18:52-04:00)
* Codex documentation (https://developers.openai.com/codex/cli/, accessed 2025-10-26T01:18:52-04:00)
* Codex getting started guide (https://help.openai.com/en/articles/11096431, accessed 2025-10-26T01:18:52-04:00)
* AI code generation best practices (https://getdx.com/blog/ai-code-enterprise-adoption/, accessed 2025-10-26T01:18:52-04:00)
## Procedure
### T1: Simple Delegation Decision (≤2k tokens)
**Steps:**
1. **Check task type** against delegation matrix (see `resources/delegation-decision-matrix.md`):
* Boilerplate/scaffold/code-generation from scratch? → Delegate to Codex
* Modification/debugging/refactoring existing code? → Keep in Claude
* Security-sensitive or requires business context? → Keep in Claude
2. **Return decision** with rationale and command (if delegating):
* If delegating → provide `codex exec --prompt "<task_description>"` command
* If keeping → explain why Claude is better suited
* Set `review_required = true` for all Codex delegations
**Token budget: ≤2k**
**Note:** For complex validation workflows with scoring matrices, use a separate validation agent. This skill focuses on fast, simple routing decisions.
## Decision Rules
### Delegate to Codex (simple criteria)
* New boilerplate generation from scratch
* Project scaffolding (REST APIs, CLIs, web apps)
* Test suite generation from specifications
* Repetitive code patterns (CRUD, data models)
* Zero or minimal existing files
* Clear natural language specifications
### Keep in Claude (simple criteria)
* Modifying existing code
* Debugging or refactoring
* Security-sensitive operations (auth, encryption, data)
* Code requiring business context or domain knowledge
* Architecture analysis or code review
* Interactive problem-solving
### Abort and escalate if:
* Task type is ambiguous or unclear
* Security implications are uncertain
* Codex CLI is not installed or authenticated
* User input validation fails
## Output Contract
**Required fields:**
```typescript
interface DelegationResult {
delegation_decision: "codex" | "claude";
rationale: string; // ≤160 chars
codex_command?: string; // required if delegation_decision = codex
review_required: boolean; // always true for codex delegations
}
```
**Validation rules:**
* `codex_command` required if delegation_decision = "codex"
* `rationale` must be ≤160 characters
* `review_required` = true for all Codex delegations
## Examples
**Example 1: Delegate to Codex (new scaffold)**
```yaml
input:
task_description: "Create a REST API for user management with CRUD operations"
task_type: generation
existing_files: []
output:
delegation_decision: codex
rationale: "New boilerplate generation from scratch"
codex_command: "codex exec --prompt 'Generate REST API for user management with CREATE, READ, UPDATE, DELETE endpoints using Express.js and TypeScript'"
review_required: true
```
**Example 2: Keep in Claude (existing code modification)**
```yaml
input:
task_description: "Fix authentication bug in login.py"
task_type: modification
existing_files: ["src/auth/login.py"]
output:
delegation_decision: claude
rationale: "Debugging existing code with security implications"
review_required: false
```
## Quality Gates
**Token budgets (enforced):**
* T1 simple delegation: ≤2k tokens (covers all use cases)
* T2/T3 not used (complex validation should use separate agent)
**Delegation quality:**
* Rationale must be ≤160 chars and actionable
* Codex commands must be syntactically valid
* All Codex delegations require manual review (`review_required = true`)
**Safety:**
* Never execute Codex commands without user confirmation
* Validate all input parameters before generating commands
* Abort if pre-checks fail (CLI not installed, auth missing)
## Resources
**Official documentation:**
* Codex CLI repository: https://github.com/openai/codex (accessed 2025-10-26T01:18:52-04:00)
* Codex CLI docs: https://developers.openai.com/codex/cli/ (accessed 2025-10-26T01:18:52-04:00)
* Codex getting started: https://help.openai.com/en/articles/11096431 (accessed 2025-10-26T01:18:52-04:00)
* AI code generation best practices: https://getdx.com/blog/ai-code-enterprise-adoption/ (accessed 2025-10-26T01:18:52-04:00)
**Local resources:**
* Delegation decision matrix: `resources/delegation-decision-matrix.md` (for detailed scoring; use separate agent for complex validation)
* Codex command reference: `resources/codex-commands.md`
* Configuration template: `resources/codex-config-template.toml`Related Skills
Gemini CLI Delegation & Large Context Routing
Fast delegation of large-context tasks to Gemini CLI via MCP when file size exceeds 100KB or task requires analysis/review.
UX Wireframe Designer
Design user experience wireframes, user flows, and interactive mockups for web and mobile applications using industry-standard notation
TypeScript Tooling Specialist
Generate TypeScript/JavaScript project scaffolding with npm/pnpm/yarn, Jest/Vitest, ESLint/Prettier, and bundling (Vite/Rollup/esbuild).
Python Tooling Specialist
Generate Python project scaffolding with Poetry/pipenv, pytest configuration, type hints (mypy), linting (ruff/black), and packaging (setuptools/flit).
Java Tooling Specialist
Generate Java project scaffolding with Maven/Gradle, JUnit 5, Mockito, Checkstyle/SpotBugs, and packaging (JAR/WAR/native-image).
C# .NET Tooling Specialist
Generate C# .NET project scaffolding with dotnet CLI, xUnit/NUnit, StyleCop analyzers, and packaging (NuGet/Docker).
Unit Testing Framework Generator
Generate unit test scaffolding and test suites for Jest, PyTest, Go testing, JUnit, RSpec with mocking, assertions, and coverage configuration
Testing Strategy Composer
Compose comprehensive testing strategies spanning unit, integration, e2e, and performance tests with optimal coverage.
Load Testing Scenario Designer
Design load testing scenarios using k6, JMeter, Gatling, or Locust with ramp-up patterns, think time modeling, and performance SLI validation.
Integration Testing Designer
Design integration test scenarios with database fixtures, external service mocks, contract testing, and test environment setup for microservices and APIs.
Chaos Engineering Experiment Designer
Design chaos engineering experiments to test system resilience with controlled failure injection, hypothesis formulation, and blast radius control.
Terraform Module Best Practices
Design reusable Terraform modules with variable validation, output schemas, module composition, and testing (Terratest).