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On larger product work, Codex can pursue technical consistency beyond what the user needs. Handling every edge case and making each path deterministic can alter what users see even when the approved outcome does not require it.
codex-workflows keeps that work within the smallest approved outcome. It confirms which user-visible behavior may change, records what must not, and requires evidence before completion. Within those boundaries, Codex chooses reversible implementation details from the repository.
The workflows are installed as Agent Skills and custom agents for OpenAI Codex CLI. The main Codex session checks scope and rough cost before design, owns progress and review decisions, and carries approved work through implementation and independent verification.
Direct Codex is the better fit for a well-scoped fix, disposable experiment, or one-shot script. It is faster and cheaper when the intended outcome and safe implementation boundary are already clear.
Use codex-workflows when technical choices can change the product scope, user-visible behavior, or a decision that needs to survive across contexts.
For example, a request to extend an existing authentication path can lead to a technically cleaner second mechanism, broader validation, and a new response contract. The frontend may adapt and the tests may pass, while users receive behavior that was never part of the approved change.
codex-workflows controls that expansion throughout the run:
| Control | What changes |
|---|---|
| Scope | The workflow compares the request with the desired outcome, explicit exclusions, the existing code, and rough implementation cost. Work that does not earn its cost is removed before it becomes architecture. |
| Phase gates | Requirements, design, and planning outputs are checked before they can authorize the next phase. Fresh agents read the approved decisions and evidence they need instead of reconstructing intent from a long conversation. |
| Execution | After implementation approval, Codex executes the task set autonomously. Each task passes its focused verification and applicable repository checks before its implementation commit. |
| Completion | Independent code and security reviews check that the completed change stays within the approved scope and has no serious problems. Required corrections return through the same implementation and quality cycle. |
This workflow uses more agent calls and tokens than direct execution. Use it when protecting the approved outcome is worth that cost.
An edge case does not require work simply because Codex can handle it. Additional validation, deterministic behavior, or a new abstraction must protect an approved requirement, an observable contract, or a demonstrated failure.
The BytePlus Seedream provider integration in mcp-image added a third external image provider across 18 files. Eight planned tasks kept the public MCP request, client, file-save, and file-URI contracts unchanged while the provider-specific implementation evolved.
Before merge, live evaluation established the final model routing, prompt limits, timeout, and response handling. Independent reviews also caught an unbounded file read, a validation bypass, a blocking FIFO path, and inconsistent API-key normalization. All four were fixed, and the PR passed 303 tests across 19 files plus a no-retry live provider call. Across the eight tasks and four fixes, the approved public contracts stayed unchanged.
Requires Node.js 22 or later and the latest Codex CLI.
cd your-project
npx codex-workflows installThen invoke a recipe in Codex CLI:
$recipe-implement Add user authentication with JWT
$ invokes a skill explicitly. Type $recipe- to see the available workflows.
| What do you need? | Start with |
|---|---|
| Deliver a backend, API, CLI, or general change end to end | $recipe-implement |
| Design first and implement later | $recipe-design → $recipe-plan → $recipe-build |
| Design and build a React / TypeScript web frontend | $recipe-front-design → $recipe-front-plan → $recipe-front-build |
| Deliver a backend and React frontend change together | $recipe-fullstack-implement |
| Review an implementation against its design | $recipe-review or $recipe-front-review |
| Define or update repository-specific quality rules | $recipe-quality-profile |
| Investigate a problem without changing code | $recipe-diagnose |
| Run a throwaway experiment or one-shot script | Use Codex directly |
flowchart LR
A[Request] --> B[Agree on the smallest useful outcome]
B --> C{One evident implementation path?}
C -->|Yes| S[Direct task cycle and security review]
S --> L[Complete]
C -->|No| D[Inspect, design, and review]
D --> E[Plan dependent work]
E --> F[Approve implementation scope]
F --> H[Per task: implement, verify, quality-check, commit]
H --> K[Independent code and security review]
K -->|Correction| H
K -->|Requirement or major design changed| B
K -->|Passed| L[Complete]
The number of independent product and design decisions determines the route, not file count or the number of edge cases Codex can identify.
| Scale | What the change needs | What happens |
|---|---|---|
| Small | One outcome that follows an existing pattern in one part of the system | Confirmed task → implementation → quality and security checks |
| Medium | One outcome that needs coordination across parts of the system or a lasting design decision | Reviewed Design Doc, plus UI Spec / ADR when required → selected integration/E2E proof → reviewed Work Plan → autonomous task cycles → final verification |
| Large | Multiple outcomes that need separate design decisions | Reviewed PRD and Design Docs, plus UI Spec / ADR when required → selected integration/E2E proof → reviewed Work Plan → autonomous task cycles → final verification |
An ADR is created only for a durable current-scope choice with at least two materially distinct options. When several choices qualify, their ADRs are reviewed together. An integration or E2E test is selected only when a cheaper test cannot prove the required interaction. Some changes need neither.
Only decisions that affect the product or repository implementation are carried forward in durable project documents. Third-party approval, production access, release execution, and unrelated operational work do not become implementation gates.
After the implementation scope is approved, the orchestrator runs the tasks, focused verification, applicable repository checks, and one implementation commit per task. It resolves problems from the approved documents and repository evidence first. User-visible behavior remains a product boundary rather than something the implementation may adjust for internal consistency. The orchestrator asks you only when progress requires a new product requirement, a change to a major approved design decision, authority only you hold, or an irreversible action you did not authorize.
Specialist agents receive the exact documents and paths needed for their work. They supply focused evidence without inheriting authority to expand the approved outcome.
Fresh contexts keep exploration, design, implementation, and review from silently sharing assumptions. The included Work Plan template ties each implementation task to its Design Doc section and acceptance criteria:
### P1-T1: Preserve the error response contract
- **Source**: `docs/design/example-design.md`, API contract, AC-2
- **Scope**: Update the repository implementation and its focused tests
- **Depends on**: none
- **Verification**: Run the contract test and observe the documented response shapeThe Task File Contract carries the source, intended result, target files, and executable verification into implementation. It adds a Verification Focus only when a test could pass without proving one important behavior. After execution, the applicable repository checks run against the complete task change before commit. Final reviewers compare the completed code with the approved documents. They also look for work outside the approved scope and serious code-quality problems. When a correction is accepted, the next review focuses on the checks that correction could affect. Run $recipe-quality-profile to define repository-specific quality rules in docs/project-context/quality.yaml for implementation and review.
- Codex CLI (latest)
- Node.js >= 22
Install into the current project:
cd your-project
npx codex-workflows installThis copies into your project:
.agents/skills/: Codex skills (foundational + recipes).codex/agents/: Subagent TOML definitions- Manifest file for tracking managed files
To make the workflows available to Codex across all projects, install them into
your user-level CODEX_HOME instead:
npx codex-workflows install --userThis installs skills into $CODEX_HOME/skills/ and agents into
$CODEX_HOME/agents/. When CODEX_HOME is not set, it defaults to ~/.codex.
# Preview what will change
npx codex-workflows update --dry-run
# Apply updates
npx codex-workflows update
# Update a user-level installation
npx codex-workflows update --userThe updater preserves files you have modified locally. It compares each file against its hash at install time and skips changed files. Versioned update history applies file moves and deletions in order, so local changes follow a moved file to its current path. Modified files retired without a replacement are moved to .codex-workflows-preserved/<version>/. New files from the update are added automatically.
# Check installed version
npx codex-workflows status
# Check a user-level installation
npx codex-workflows status --userInvoke recipes with $recipe-name in Codex. Type $recipe- and use tab completion to see all available recipes.
View all recipe entry points
| Recipe | What it does | When to use |
|---|---|---|
$recipe-implement |
Full lifecycle with layer routing (backend/frontend/fullstack) | New features (universal entry point) |
$recipe-task |
Single task with rule selection | Bug fixes, small changes |
$recipe-design |
Requirements → scale-selected product and design documents | Product and architecture design |
$recipe-plan |
Design Doc → selective integration/E2E skeletons → work plan | Planning phase from an approved Design Doc |
$recipe-prepare-implementation |
Prepare existing repository-local tools needed by an approved Work Plan | Explicit setup request or a concrete task capability is unavailable |
$recipe-build |
Execute backend tasks with validation between steps | Resume backend implementation |
$recipe-review |
Review implementation scope, Design Doc compliance, code quality, and security; apply corrections approved by the user | Post-implementation check |
$recipe-quality-profile |
Define or update repository-specific quality rules in docs/project-context/quality.yaml |
Set up or maintain quality rules |
$recipe-diagnose |
Problem investigation → failure-point verification → solution | Bug investigation |
$recipe-reverse-engineer |
Generate PRD + Design Docs from existing code | Legacy system documentation |
$recipe-add-integration-tests |
Add integration/E2E tests from Design Doc | Test coverage for existing code |
$recipe-update-doc |
Update existing Design Doc / PRD / ADR with review | Spec changes, document maintenance |
| Recipe | What it does | When to use |
|---|---|---|
$recipe-front-design |
Requirements → scale-selected UI and design documents | Frontend product and architecture design |
$recipe-front-adjust |
Focused UI adjustment using repository, supplied, or required external evidence | Focused UI changes after implementation |
$recipe-front-plan |
Frontend Design Doc → selective integration/E2E skeletons → work plan | Frontend planning phase |
$recipe-front-build |
Execute frontend tasks with focused verification and quality checks | Resume frontend implementation |
$recipe-front-review |
Review frontend scope, compliance, code quality, and security; apply React corrections approved by the user | Frontend post-implementation check |
| Recipe | What it does | When to use |
|---|---|---|
$recipe-fullstack-implement |
Full lifecycle with separate Design Docs per layer | Cross-layer features |
$recipe-fullstack-build |
Execute tasks with layer-aware agent routing | Resume cross-layer implementation |
Recipes use docs/plans/ as ephemeral working state for Work Plans, implementation Task Files, and temporary review-fix or test-addition Task Files. Task and phase progress is updated there after each quality-approved implementation commit, while those progress files stay outside that commit. Add the directory to your project's .gitignore unless your team intentionally wants to review those transient files:
docs/plans/PRDs, ADRs, UI Specs, and Design Docs are durable project documents and are intended to be committed.
Recipes load the repository-aware guidance required for the current task. You rarely need to select these skills directly.
View foundational skills
| Skill | What it provides |
|---|---|
coding-rules |
Code quality, function design, error handling, refactoring |
testing |
Proportionate TDD, observable proof selection, test integrity, and repository-required verification |
ai-development-guide |
Evidence-backed root cause, proportionate impact analysis, and applicable quality assurance |
reviewee-judgment |
Evidence-backed evaluation of received findings before they generate revision work |
documentation-criteria |
Document creation rules and templates (PRD, ADR, Design Doc, Work Plan) |
requirement-convergence |
Outcome, requirement layers, user-decided exclusions, and rough cost before design |
implementation-approach |
Direct MVP, evidence-backed expansion, subtraction, slicing, and verification boundary |
integration-e2e-testing |
Selecting and designing only integration/E2E tests that prove a necessary real interaction |
external-resource-context |
Focused resolution of one external evidence source required by a current decision |
llm-friendly-context |
Clear prompts, handoffs, generated artifacts, task files, and review findings for downstream agents |
task-analyzer |
Task intent analysis, task type classification, skill selection |
subagents-orchestration-guide |
Multi-agent coordination, workflow flows, guided autonomous execution |
Web-frontend references are included for TypeScript used in web frontend work, including React applications (coding-rules/references/typescript.md, testing/references/typescript.md). They do not apply to backend TypeScript.
Codex spawns these as needed during recipe execution. You do not need to learn them first; recipes route domain work to the relevant agents while the orchestrator retains workflow control. Each agent runs in its own context with specialized instructions and explicitly named required skills.
View all specialized agent roles
| Agent | Role |
|---|---|
requirement-analyzer |
Compact request signals plus repository-backed scope and cost evidence for orchestrator decisions |
prd-creator |
PRD creation and structuring |
technical-designer |
Complete ADR-batch or Design Doc creation (backend/general) |
technical-designer-frontend |
Complete frontend ADR-batch or Design Doc creation (React) |
ui-spec-designer |
UI Specification from PRD and optional prototype code |
codebase-analyzer |
Compact repository facts for later technical decisions, minimal design, and verification |
ui-analyzer |
UI facts from external resources (design tools, design-system docs, deployed UI) and frontend code |
work-planner |
Work plan creation from Design Docs |
document-reviewer |
Document review against governing requirements and design decisions |
design-sync |
Cross-document consistency verification |
| Agent | Role |
|---|---|
task-decomposer |
Work plan → the fewest executable implementation task files |
task-executor |
Task-file implementation with focused verification (backend) |
task-executor-frontend |
React implementation with applicable behavior-focused RTL verification |
quality-fixer |
Applicable repository checks and in-scope quality repair (backend) |
quality-fixer-frontend |
Applicable React, TypeScript, RTL, and bundle checks and repair |
acceptance-test-generator |
Selected integration/E2E test skeleton generation |
integration-test-reviewer |
Test quality review |
| Agent | Role |
|---|---|
code-reviewer |
Checks the completed implementation against the approved scope and documents, and flags serious code-quality problems |
code-verifier |
Document-code consistency verification |
security-reviewer |
Security compliance review after implementation |
rule-advisor |
Skill selection for standalone work not already governed by a recipe |
scope-discoverer |
Codebase scope discovery for reverse docs, including PRD unit grouping |
technical-spike |
Bounded empirical evidence for one design-changing effect or cost |
| Agent | Role |
|---|---|
investigator |
Evidence collection, path mapping, and failure-point discovery |
verifier |
Path coverage validation and independent failure-point evaluation |
solver |
Solution derivation with tradeoff analysis |
After installation, your project gets:
View installed layout
your-project/
├── .agents/skills/ # Codex skills
│ ├── coding-rules/ # Foundational guidance
│ ├── testing/
│ ├── ai-development-guide/
│ ├── reviewee-judgment/
│ ├── documentation-criteria/
│ ├── requirement-convergence/
│ ├── implementation-approach/
│ ├── integration-e2e-testing/
│ ├── external-resource-context/
│ ├── llm-friendly-context/
│ ├── task-analyzer/
│ ├── subagents-orchestration-guide/
│ └── recipe-*/ # Workflow entry points ($recipe-*)
├── .codex/agents/ # Subagent TOML definitions
│ ├── requirement-analyzer.toml
│ ├── technical-designer.toml
│ ├── ui-analyzer.toml
│ ├── task-executor.toml
│ └── ... (26 agents total)
└── docs/ # Created as you use the recipes
├── prd/
├── design/
├── adr/
├── ui-spec/
└── plans/
└── tasks/
When a product idea still needs discovery or validation, Nautilus can test the assumptions behind it and turn the results into a PRD. Pass the approved PRD to $recipe-implement or $recipe-design.
If requirements already live in Linear or an existing PRD, linear-prism can read the codebase, split the work into implementation-ready Linear issues, and record blocking relationships. Use an approved issue as input to $recipe-design.
Q: What models does this work with?
A: Designed for current GPT models. Models are configurable per agent in the TOML files.
Q: Can I customize the agents?
A: Yes. Edit the TOML files in .codex/agents/ to change model, sandbox_mode, or developer_instructions. Each agent names its required skills in developer_instructions. Files you modify locally are preserved during npx codex-workflows update.
For a user-level installation, edit the files in $CODEX_HOME/agents/ and use
npx codex-workflows update --user. User-level files modified after installation
are preserved in the same way.
Q: What's the difference between $recipe-implement and $recipe-fullstack-implement?
A: $recipe-implement is the universal entry point. It runs requirement-analyzer first, uses the request and repository scope to identify affected layers, and automatically routes to backend, frontend, or fullstack flow. $recipe-fullstack-implement skips the detection and goes straight into the fullstack flow (separate Design Docs per layer, design-sync, layer-aware task execution). Use $recipe-implement when you're not sure; use $recipe-fullstack-implement when you know upfront that the feature spans both layers.
Q: Does this work with MCP servers?
A: Yes. Codex skills and subagents work alongside MCP. Skills operate at the instruction layer, while MCP operates at the tool transport layer. Custom agents inherit parent mcp_servers when the agent TOML omits mcp_servers; add agent-local MCP config only for agent-specific servers or tool filtering.
Q: How is this related to claude-code-workflows?
A: claude-code-workflows is the Claude Code counterpart. The repositories share the same workflow philosophy, adapted to each tool's native extension points. They can coexist in the same project because codex-workflows installs its agent definitions under .codex/agents/ and Claude Code uses its own .claude/ files.
Q: What if a subagent seems stuck?
A: The main Codex session owns progress. It inspects the returned evidence, retries or repairs unusable results, and continues unaffected work. A subagent result does not stop the workflow by itself.
Background reading behind the workflow design
- Why LLMs Are Bad at 'First Try' and Great at Verification: why review loops and session separation are more reliable than first-shot generation on complex work
- When Better Models Make Old Agent Workflows Worse: why workflow constraints should protect boundaries and evidence without prescribing the model's internal path
- Reasoning Effort Is Not a Quality Setting: why broader technical exploration is useful only when the phase can select and discard the extra work it finds
- Stop Putting Everything in AGENTS.md: why
AGENTS.mdshould stay lean while rules, docs, and task instructions live near the point of use
MIT License. Free to use, modify, and distribute.
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