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codex-claude-executor-framework

Codex-controlled Claude Code executor workflow with DeepSeek API, demo, and reusable skill

Set up

Skills are installed by placing their folder where your agent loads skills.

The download comes from github.com/dengls24/codex-claude-executor-framework itself, not from our server, so what you get is exactly what its author published.

Install instructions come from the README

Skills do not use an MCP config. Follow the steps in the README below.

README

synced Oct 26, 2026

Codex-Claude Executor Framework

A usage-aware and capability-aware multi-tool workflow for local coding experiments.

This repository provides a reference implementation of a broader method: use durable task artifacts to route work across multiple AI coding tools by capability, remaining usage, marginal cost, risk, and verifiability.

The implemented demo uses:

  • Codex as the principal planner, permission judge, and final verifier.
  • Claude Code + DeepSeek API as a lower-cost delegated adviser, executor, and reviewer.

That pairing is only one case. The same method also applies when a user has two comparable monthly subscriptions, or any mixture of coding agents, writing models, API models, local scripts, CI, and human reviewers.

Core Idea

Do not move context by repeatedly pasting long chat summaries between models. Instead, persist context as auditable files:

TASK.md              portable task specification
CLAUDE_ADVICE.md     independent planning critique
RESULT.md            execution report
CLAUDE_REVIEW.md     independent review
run-summary.json     execution metadata
test logs            verification evidence

The stronger or scarcer model spends its budget on decisions that are hard to verify. The cheaper or more available model spends its budget on work that is easy to verify.

Why This Matters

Users often subscribe to several AI tools at once. A common failure pattern is:

Use Model A until usage runs out
-> manually summarize context
-> restart in Model B
-> lose decisions, failed attempts, file state, and validation history

This framework replaces that with:

Persist context in TASK.md
-> route the next step to the best available tool
-> require structured output
-> verify with tests and diff inspection

The result is lower context migration cost, better quota utilization, and clearer accountability.

Two Primary Cases

Case A: Strong Principal + Cheap Executor

This is the current reference implementation. Codex Pro is stronger and better suited for planning, safety decisions, and final acceptance. Claude Code with DeepSeek API is cheaper but weaker, so it is used for bounded execution loops when validation is available.

flowchart TD
    U[User goal] --> C[Codex Pro principal]
    C --> T[TASK.md]
    T --> A[Claude Code + DeepSeek advise]
    A --> AD[CLAUDE_ADVICE.md]
    AD --> C
    C --> E[Claude Code + DeepSeek execute]
    E --> R[RESULT.md]
    E --> D[Code diff]
    R --> RV[Claude Code + DeepSeek review]
    D --> RV
    RV --> CR[CLAUDE_REVIEW.md]
    CR --> C
    D --> C
    C --> TEST[Codex runs tests and inspects diff]
    TEST --> DECIDE{Accept?}
    DECIDE -->|Yes| DONE[Ship]
    DECIDE -->|No| RETRY[Narrow task and retry]
    RETRY --> E

Decision rule:

  • Use Codex for architecture, risk judgment, permissions, and final verification.
  • Use Claude Code + DeepSeek for repetitive edits, debug loops, and second opinions.
  • Accept nothing until Codex or deterministic tests verify the result.

Case B: Comparable Monthly Subscriptions

This case is not about one model being much cheaper. It is about two or more tools with similar monthly plans but separate usage limits. The goal is to avoid exhausting one tool and then paying a large context migration cost.

flowchart TD
    G[User goal] --> S[Portable task state: TASK.md]
    S --> Q{Quota and role fit}
    Q -->|Tool A low usage remaining| B[Route next step to Tool B]
    Q -->|Tool B low usage remaining| A[Route next step to Tool A]
    Q -->|Both healthy| F{Best role fit?}
    F -->|Planning| P[Best planner]
    F -->|Execution loop| E[Best executor]
    F -->|Independent critique| R[Best reviewer]
    A --> O[Structured artifacts]
    B --> O
    P --> O
    E --> O
    R --> O
    O --> V[Separate verifier]
    V --> D{Validated?}
    D -->|Yes| DONE[Accept]
    D -->|No| N[Revise TASK.md and reroute]
    N --> Q

Decision rule:

  • Balance tools by remaining subscription usage before a quota emergency happens.
  • Route tasks by role fit, not brand loyalty.
  • Keep final verification separate from the agent that made the edit.
  • Use TASK.md as the portable context layer so switching tools is cheap.

General Multi-Tool Flow

The framework generalizes beyond Codex and Claude:

flowchart LR
    U[User] --> P[Principal or planner]
    P --> T[TASK.md]
    T --> X{Route by capability, quota, cost, risk}
    X --> EX[Executor]
    X --> RV[Reviewer]
    X --> WR[Writer]
    EX --> ART[Artifacts and diff]
    RV --> ART
    WR --> ART
    ART --> VF[Verifier: Codex, tests, CI, or human]
    VF --> OUT{Accept or retry}
    OUT -->|Accept| DONE[Done]
    OUT -->|Retry| T

Possible role assignments:

RoleResponsibilityExample tools
PrincipalOwns goals, constraints, safety, and final acceptanceCodex Pro, senior human, strongest coding agent
PlannerConverts intent into TASK.mdCodex, GPT Pro, Claude
ExecutorPerforms bounded implementation loopsClaude Code, Codex CLI, cheaper API model
ReviewerGives independent critiqueAny second model or human reviewer
WriterProduces polished prose or slidesGPT Pro, Claude, domain writing model
VerifierRuns tests and audits filesCodex, CI, scripts, human

Implemented Modes

The bundled Codex skill supports three Claude delegation modes:

ModePurposeWritesEdits code?
adviseIndependent task analysis, risks, and validation planCLAUDE_ADVICE.mdNo
executeScoped implementation and requested validationRESULT.mdYes
reviewIndependent review of diff, logs, and resultCLAUDE_REVIEW.mdNo

Recommended loop:

Codex plan -> Claude advise -> Codex revise task -> Claude execute -> Claude review -> Codex final verification

Repository Layout

.
|-- README.md
|-- docs/
|   |-- paper.md
|   |-- manual.md
|   |-- scheduler.md
|   |-- generalized-framework.md
|   |-- methodology.md
|   `-- workflow.md
|-- demo/
|   |-- TASK.md
|   |-- stats_utils.py
|   |-- test_stats_utils.py
|   |-- CLAUDE_ADVICE.md
|   |-- RESULT.md
|   `-- CLAUDE_REVIEW.md
|-- skills/
|   `-- claude-executor/
|       |-- SKILL.md
|       |-- agents/openai.yaml
|       `-- scripts/
|           |-- Set-ClaudeExecutor.ps1
|           `-- Invoke-ClaudeExecutor.ps1
`-- scripts/
    `-- install-skill.ps1

Quick Start

Prerequisites:

  • Windows PowerShell
  • Git
  • Claude Code CLI installed
  • Claude Code configured to use DeepSeek API through an Anthropic-compatible endpoint

Install the skill into your local Codex skills folder:

& ".\scripts\install-skill.ps1"

Enable the executor with a small budget:

& "$HOME\.codex\skills\claude-executor\scripts\Set-ClaudeExecutor.ps1" -Enabled $true -MaxBudgetUsd 0.20 -PermissionMode auto

Run the demo workflow:

& "$HOME\.codex\skills\claude-executor\scripts\Invoke-ClaudeExecutor.ps1" `
  -Mode advise `
  -TaskPath ".\demo\TASK.md" `
  -Workspace ".\demo"

& "$HOME\.codex\skills\claude-executor\scripts\Invoke-ClaudeExecutor.ps1" `
  -Mode execute `
  -TaskPath ".\demo\TASK.md" `
  -Workspace ".\demo"

& "$HOME\.codex\skills\claude-executor\scripts\Invoke-ClaudeExecutor.ps1" `
  -Mode review `
  -TaskPath ".\demo\TASK.md" `
  -Workspace ".\demo"

Then verify independently:

cd .\demo
python -m unittest

Disable after use:

& "$HOME\.codex\skills\claude-executor\scripts\Set-ClaudeExecutor.ps1" -Enabled $false

Documentation

  • Academic-style paper: problem statement, architecture, workflow, evaluation criteria, and limitations.
  • User manual: installation, task writing, three-pass usage, recovery, and verification.
  • Usage-aware scheduler: routing based on usage, cost, risk, and model strengths.
  • Generalized framework: extension beyond Codex + Claude/DeepSeek to any multi-tool setup.
  • Methodology: role separation and acceptance rule.
  • Workflow: state machine, permission strategy, and run artifacts.

Demo Result

The included demo fixes a small Python function:

  • summarize([1, None, 3, 5]) should ignore None.
  • Empty or all-None input should raise ValueError.
  • Claude proposes the fix, implements it, and reviews the result.
  • Codex independently runs python -m unittest and accepts only after tests pass.

Observed local validation:

Ran 2 tests in 0.001s

OK

Safety Model

  • Default config is disabled.
  • Claude is never treated as authoritative.
  • No API keys are stored in this repo.
  • Runtime config is written outside the repo at:
$HOME\.codex\claude-executor\config.json
  • Avoid --dangerously-skip-permissions and bypassPermissions.
  • Prefer branch or worktree isolation for non-trivial tasks.
  • Review git diff and rerun tests before accepting any result.

License

MIT

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