AI-powered code analysis, refactoring, and automated editing via Codex CLI with GPT-5.2.
Works with
Runs codex exec and codex resume commands with configurable reasoning effort ( xhigh , high , medium , low ) and sandbox modes (read-only, workspace-write, danger-full-access)
Defaults to GPT-5.2 model (76.3% SWE-bench performance); supports gpt-5.2-max, gpt-5.2-mini, and gpt-5.1-thinking for different complexity and cost trade-offs
Session continuity: resume prior Codex work at any time using co
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncodexExecute the skills CLI command in your project's root directory to begin installation:
Fetches codex from softaworks/agent-toolkit and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate codex. Access via /codex in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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gpt-5.2 model. Ask the user (via AskUserQuestion) which reasoning effort to use (xhigh,high, medium, or low). User can override model if needed (see Model Options below).--sandbox read-only unless edits or network access are necessary.-m, --model <MODEL>--config model_reasoning_effort="<high|medium|low>"--sandbox <read-only|workspace-write|danger-full-access>--full-auto-C, --cd <DIR>--skip-git-repo-checkcodex exec --skip-git-repo-check resume --last via stdin. When resuming don't use any configuration flags unless explicitly requested by the user e.g. if he species the model or the reasoning effort when requesting to resume a session. Resume syntax: echo "your prompt here" | codex exec --skip-git-repo-check resume --last 2>/dev/null. All flags have to be inserted between exec and resume.2>/dev/null to all codex exec commands to suppress thinking tokens (stderr). Only show stderr if the user explicitly requests to see thinking tokens or if debugging is needed.| Use case | Sandbox mode | Key flags |
|---|---|---|
| Read-only review or analysis | read-only |
--sandbox read-only 2>/dev/null |
| Apply local edits | workspace-write |
--sandbox workspace-write --full-auto 2>/dev/null |
| Permit network or broad access | danger-full-access |
--sandbox danger-full-access --full-auto 2>/dev/null |
| Resume recent session | Inherited from original | echo "prompt" | codex exec --skip-git-repo-check resume --last 2>/dev/null (no flags allowed) |
| Run from another directory | Match task needs | -C <DIR> plus other flags 2>/dev/null |
| Model | Best for | Context window | Key features |
|---|---|---|---|
gpt-5.2-max |
Max model: Ultra-complex reasoning, deep problem analysis | 400K input / 128K output | 76.3% SWE-bench, adaptive reasoning, $1.25/$10.00 |
gpt-5.2 ⭐ |
Flagship model: Software engineering, agentic coding workflows | 400K input / 128K output | 76.3% SWE-bench, adaptive reasoning, $1.25/$10.00 |
gpt-5.2-mini |
Cost-efficient coding (4x more usage allowance) | 400K input / 128K output | Near SOTA performance, $0.25/$2.00 |
gpt-5.1-thinking |
Ultra-complex reasoning, deep problem analysis | 400K input / 128K output | Adaptive thinking depth, runs 2x slower on hardest tasks |
GPT-5.2 Advantages: 76.3% SWE-bench (vs 72.8% GPT-5), 30% faster on average tasks, better tool handling, reduced hallucinations, improved code quality. Knowledge cutoff: September 30, 2024.
Reasoning Effort Levels:
xhigh - Ultra-complex tasks (deep problem analysis, complex reasoning, deep understanding of the problem)high - Complex tasks (refactoring, architecture, security analysis, performance optimization)medium - Standard tasks (refactoring, code organization, feature additions, bug fixes)low - Simple tasks (quick fixes, simple changes, code formatting, documentation)Cached Input Discount: 90% off ($0.125/M tokens) for repeated context, cache lasts up to 24 hours.
codex command, immediately use AskUserQuestion to confirm next steps, collect clarifications, or decide whether to resume with codex exec resume --last.echo "new prompt" | codex exec resume --last 2>/dev/null. The resumed session automatically uses the same model, reasoning effort, and sandbox mode from the original session.codex --version or a codex exec command exits non-zero; request direction before retrying.--full-auto, --sandbox danger-full-access, --skip-git-repo-check) ask the user for permission using AskUserQuestion unless it was already given.AskUserQuestion.Requires Codex CLI v0.57.0 or later for GPT-5.2 model support. The CLI defaults to gpt-5.2 on macOS/Linux and gpt-5.2 on Windows. Check version: codex --version
Use /model slash command within a Codex session to switch models, or configure default in ~/.codex/config.toml.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
I recommend codex for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: codex is focused, and the summary matches what you get after install.
codex fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: codex is focused, and the summary matches what you get after install.
I recommend codex for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added codex from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
codex is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: codex is the kind of skill you can hand to a new teammate without a long onboarding doc.
codex reduced setup friction for our internal harness; good balance of opinion and flexibility.
codex fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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