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    gpt-cmdr

    dev-invoke-codex-cli

    gpt-cmdr/dev-invoke-codex-cli
    AI & ML
    40

    About

    SKILL.md

    Install

    Install via Skills CLI

    or add to your agent
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    ├─
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    └─

    About

    Delegate code tasks to OpenAI Codex CLI using markdown file handoff pattern. Write instructions to TASK.md, Codex reads and executes, outputs to OUTPUT.md. Use for implementation, refactoring, code...

    SKILL.md

    Invoking Codex CLI

    Claude-only orchestration skill. This skill exists to let Claude delegate out to Codex CLI. It is excluded from any future shared multi-harness skill corpus.

    Delegate tasks to Codex CLI using markdown files for instruction input and deliverable output. Write instructions to TASK.md, invoke Codex, then read OUTPUT.md for results.

    Pattern: Markdown File Handoff

    Claude Code                         Codex CLI
        |                                   |
        +-- Write TASK.md ------------------+
        |   (instructions + context)        |
        |                                   |
        +-- Execute: codex e "Read TASK.md, |
        |   follow instructions, write      |
        |   deliverables to OUTPUT.md"      |
        |                                   |
        |                                   +-- Reads TASK.md
        |                                   +-- Executes task
        |                                   +-- Writes OUTPUT.md
        |                                   |
        +-- Read OUTPUT.md <----------------+
        |   (deliverables + results)        |
        v                                   v
    

    Benefits:

    • Eliminates shell escaping issues (quotes, special characters, code blocks)
    • Keeps context structured in reviewable files
    • Enforces explicit deliverable format
    • Supports session resume via thread ID

    When to Use

    Use this skill for:

    • Complex implementation requiring multi-file changes
    • Refactoring with dependency tracking
    • Code generation with detailed specifications
    • Tasks requiring extended thinking (20-30 minutes)

    Model Selection

    Model: Always use gpt-5.2-codex (latest model).

    Reasoning Effort: Adjust based on task complexity.

    Reasoning Effort Use Case Speed
    xhigh Default. Complex tasks, deep analysis Slowest, best quality
    high Medium complexity, good reasoning Balanced
    medium Lighter tasks, adequate reasoning Faster
    low Simple tasks, quick response Fastest

    Recommendation: Use default xhigh reasoning for most tasks. Lower reasoning effort for simpler tasks instead of switching to older models.

    Invocation

    Standard Pattern (Recommended)

    codex e "Read TASK.md in the current directory. Follow the instructions exactly. Write all deliverables to OUTPUT.md." \
      -C "/path/to/project" \
      --full-auto \
      --skip-git-repo-check
    

    With Lower Reasoning Effort

    # For simpler tasks, reduce reasoning effort (not model)
    codex e "Read TASK.md, follow instructions, write results to OUTPUT.md" \
      -C "/path/to/project" \
      -c model_reasoning_effort=medium \
      --full-auto \
      --skip-git-repo-check
    

    Resume Session

    codex e resume <thread_id> "Read TASK.md for updated instructions, append results to OUTPUT.md"
    

    Core Flags Reference

    Flag Purpose
    -C /path Working directory (where TASK.md lives)
    --full-auto Sandboxed auto-execution (workspace-write + no approvals)
    --skip-git-repo-check Work in any directory
    -c model_reasoning_effort=<level> Reasoning: xhigh (default), high, medium, low

    Model: Always gpt-5.2-codex (latest). Adjust reasoning effort instead of changing models.

    Task File Template (TASK.md)

    # Task: [Brief Title]
    
    ## Objective
    [Clear statement of what needs to be accomplished]
    
    ## Context
    [Relevant background, constraints, requirements]
    
    ## Input Files
    - `src/api/users.ts` - User service to modify
    - `src/types/user.ts` - Type definitions
    
    ## Instructions
    1. [First step]
    2. [Second step]
    3. [Third step]
    
    ## Deliverables
    Write to OUTPUT.md:
    - Summary of changes made
    - List of files modified
    - Any issues encountered
    - Recommendations for follow-up
    - Thread ID for session resume
    
    ## Constraints
    - Do not modify files outside src/api/
    - Maintain backward compatibility
    - Follow existing code style
    

    Output File Template (OUTPUT.md)

    Instruct Codex to produce:

    # Deliverables: [Task Title]
    
    ## Summary
    [Brief description of what was done]
    
    ## Changes Made
    
    ### Files Modified
    | File | Change |
    |------|--------|
    | `src/api/users.ts` | Added validation logic |
    
    ### Code Changes
    [Key code snippets if relevant]
    
    ## Issues Encountered
    - [Any problems and how resolved]
    
    ## Recommendations
    - [Suggested follow-up actions]
    
    ## Session
    Thread ID: `<thread_id>` (for resume)
    

    Workflow Example (ras-commander)

    1. Write TASK.md

    # Task: Add Validation to Precipitation API
    
    ## Objective
    Add depth conservation validation to precipitation methods.
    
    ## Context
    The precipitation methods in ras_commander/precip/ need validation
    to ensure depth conservation at 10^-6 precision.
    
    ## Input Files
    - `ras_commander/precip/Atlas14Storm.py`
    - `ras_commander/precip/StormGenerator.py`
    
    ## Instructions
    1. Add depth conservation check after hyetograph generation
    2. Raise ValidationError if conservation fails
    3. Log successful validation with actual precision achieved
    
    ## Deliverables
    Write to OUTPUT.md:
    - Summary of validation logic added
    - Files modified with line references
    - Test cases to validate
    
    ## Constraints
    - Use existing ValidationSeverity pattern
    - Maintain backward compatibility
    

    2. Execute Codex

    codex e "Read TASK.md, follow the instructions, write deliverables to OUTPUT.md" \
      -C "C:/GH/ras-commander" \
      --full-auto \
      --skip-git-repo-check
    

    3. Read OUTPUT.md

    Parse the results, verify changes, and continue the workflow.

    Environment Variables

    CODEX_API_KEY=sk-xxx      # Required (or use codex login)
    OPENAI_API_KEY=sk-xxx     # Alternative
    

    Session Management

    • Thread ID appears in Codex console output at session start
    • Request thread ID in OUTPUT.md deliverables section
    • Resume with: codex e resume <thread_id> "follow-up instruction"

    Tips

    1. Be explicit in TASK.md - Include all context, don't assume
    2. Specify output structure - Tell Codex exactly what OUTPUT.md should contain
    3. List input files - Explicitly name files Codex should read
    4. Define constraints - Prevent unwanted modifications
    5. Request thread ID - Include in deliverables for session resume
    6. Use default model - gpt-5.2-codex is best for complex reasoning tasks

    When to Escalate

    Use Codex for:

    • Implementation requiring extended thinking
    • Multi-file refactoring
    • Complex code generation
    • Architecture planning

    Use specialized ras-commander agents for:

    • HDF analysis -> hdf-analyst
    • Geometry parsing -> geometry-parser
    • USGS integration -> usgs-integrator

    Cross-References

    Agents (delegate when needed):

    • code-oracle-codex -- Delegate for deep code analysis with Codex

    Skills (related workflows):

    • qa_review_triple-model -- Legacy provider-mixed workflow; explicit user request only
    Recommended Servers
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    Repository
    gpt-cmdr/ras-commander
    Files