plugin-creator: One-click Scaffold Codex Plugin with Official Skill
# Official OpenAI System Skill Plugin-Creator: Guide This article introduces OpenAI's official Skill Plugin-Creator system, detailing how to scaffold plugin directories for Codex/ChatGPT, generate the required `.codex-plugin/plugin.json` file, create placeholders for skills, hooks, MCP, apps as needed, and write configurations to local or repository-level `marketplace.json`. It also covers conversational invocation methods (`$plugin-creator` / `@plugin-creator`), command parameters for `create_basic_plugin.py`, conventions for manifest and marketplace fields, applicable scenarios, and common pitfalls.
Read More# skill-installer: The "Package Manager" for Installing Skills on Codex
Skill-installer is a system Skill pre-installed by OpenAI alongside Codex, used to install Skills to `$CODEX_HOME/skills` (default path: `~/.codex/skills`) from the official curated/experimental catalog or any GitHub repository path. Based on the official SKILL.md and Codex documentation, this article explains how to use `skill-installer` to list and install Skills, covers script parameters, private repository and download fallback strategies, as well as the boundaries of local testing and plugins distribution.
Read MoreBuild ChatGPT Apps with chatgpt-apps Skill: MCP Server + Widget UI
### 正式翻译结果： ### Introduction to OpenAI's official curated Skill chatgpt-apps: How to scaffold, refactor and troubleshoot ChatGPT Apps SDK applications (MCP server + Widget UI) following a docs-first workflow. The article verifies the capabilities of Skills, application prototype classification, upstream example priority, usage boundaries between MCP Apps bridge and window.openai, as well as the installation and activation methods in Codex and Cursor. It also provides prompt examples for paired use with openai-docs and local joint debugging steps for Developer Mode.
Read More`define-goal`: Clarify the Goal First, Then Let the Agent Take Action
This article introduces OpenAI's curated Skill `define-goal`: it is used to refine vague intentions into specific, measurable and verifiable goals before coding, and call `get_goal/create_goal` again in accordance with quality standards. Based on the official SKILL.md documentation, the article explains the workflow, comparisons between good and bad goals, Codex installation (via `$skill-installer`), and the method of enabling it in tools such as Cursor/Claude Code through the SKILL.md directory. It also reminds that this skill only performs goal definition and does not manage long-cycle execution deliverables.
Read MoreTurn Notion research into cited structured documents with notion-research-documentation
### Official English Translation: This article introduces the OpenAI curated skill `notion-research-documentation`: under the premise that Notion MCP has been connected, it enables cross-page retrieval and evidence synthesis within Notion, and generates cited documents in templates such as briefings, summaries, comparisons, and full reports. It follows the official SKILL.md instructions for installation and activation (including Codex's `$skill-installer` and Cursor's skills directory), covers the official five-step workflow, competitive product comparison examples, as well as precautions such as permissions, timeliness, and warehouse deprecation.
Read MoreUse notion-spec-to-implementation to split Notion PRD into executable plans
### 译文： This article introduces OpenAI curated skill `notion-spec-to-implementation`: with the support of Notion MCP, it parses PRD/functional specifications into implementation plans, 1-2 day granular tasks and progress write-back, realizing the connection between Spec ↔ Plan ↔ Tasks. The article verifies the installation methods (Codex $skill-installer and Skills directory of Cursor/Claude Code), MCP configuration (mcp.notion.com), workflows and official API examples, and explains applicable scenarios and common precautions.
Read MoreEquip Agents with "Eyes" Using Screenshot Skill: Desktop Screenshot and Visual QA
# OpenAI Curated Screenshot Agent Skill This skill enables agents to capture full-screen, window-specific, or pixel-region screenshots across macOS, Linux and Windows for visual analysis and UI validation. It prioritizes tools like Figma and Playwright first, with system-level screenshots as a fallback. The article details its save path rules, official installation methods (using Codex's $skill-installer and placing files in Cursor/Claude Code directories), cross-platform script usage, as well as considerations around permissions, dependencies and multi-monitor setups, helping to build a complete front-end visual QA workflow that connects design mockups, browser pages and desktop applications.
Read More`playwright-interactive: Using Persistent JS_REPL for UI Iteration and Debugging`
# Introduction to OpenAI's Featured Skill: playwright-interactive This skill enables persistent handling of Playwright/Electron via js_repl, allowing rapid iterative UI debugging on local web and Electron applications. It also supports completing QA checklists, functional validation, visual QA and viewport adaptation following official workflows. This article details the installation steps, pre-configuration requirements, typical code snippets, as well as notes such as the possible removal of js_repl in the current Codex, and makes a comparison with the CLI-oriented Playwright Skill.
Read More# Figma-Create-Design-System-Rules: Develop Project-Specific Design System Rules for Agents
This is an introduction to `figma-create-design-system-rules` in the openai/skills curated catalog: On the premise of connecting Figma MCP, it analyzes the codebase and generates project-level design system rules, constraining component paths, Design Tokens, styling solutions and the Figma-to-code workflow, and writes them into `CLAUDE.md`, `AGENTS.md` or `.cursor/rules/figma-design-system.mdc` respectively, to alleviate problems such as random use of spacing, hard-coded colors, and repeated creation of components when AI implements UI. The article verifies the installation method, five-step workflow and precautions.
Read MoreUse figma-generate-design to reverse-generate pages from code into Figma
This article introduces the `figma-generate-design` Skill in the OpenAI curated and Figma MCP ecosystems: on the premise that Figma MCP is connected and the target file has a design system, it writes application pages or multi-block layouts into Figma in the form of component instances and Tokens, and forcibly cooperates with `figma-use`. The article verifies official processes including plugin installation (Cursor / Claude Code / Codex), npx skills installation method, block assembly and parallel calibration of `generate_figma_design`, as well as the boundaries between adjacent Skills such as `figma-implement-design` and Code Connect.
Read MoreVisualize Security Responsibility Topology from Git History Using security-ownership-map
# Security-Ownership-Map: An OpenAI Curated Agent Skill Security-Ownership-Map is an OpenAI curated Agent Skill that constructs human-file bipartite graphs and covariation clustering based on Git history, calculates the Bus Factor of sensitive code, and supports output in CSV/JSON formats (with optional Neo4j/Gephi exports). This article introduces its positioning, installation and activation, usage of `run_ownership_map` and `query_ownership`, sensitive code rules and applicable boundaries, which is suitable for enterprise security teams to conduct inventory of ownership drift and orphaned sensitive code.
Read More# 翻译结果： security-threat-model: Let Agent perform threat modeling based on code repositories
### Official Translation: This article introduces OpenAI's curated Skill **security-threat-model**: it enumerates trust boundaries, assets, attacker capabilities and abuse paths based on repository evidence, and outputs a structured Markdown threat model. The article verifies the official workflow, reporting contract, installation and activation methods of Codex/Cursor/Claude Code (including the Trail of Bits plugin), as well as typical prompt words and usage boundaries.
Read More`render-deploy`: Analyze codebase, generate Blueprint, and deploy applications to Render
This article introduces OpenAI Curated Agent Skill `render-deploy`: it analyzes the codebase to generate a render.yaml Blueprint, or directly creates a single service via Render MCP, and provides a deep link to the Dashboard to complete the deployment. It verifies the installation methods (npx skills / Codex skill-installer), the MCP configuration for Cursor/Claude/Codex, the heuristic guidelines for choosing between Blueprint and Direct Creation, as well as precautions such as Git remote, image service restrictions, `sync:false` for secrets, port binding and other matters, and complements deployment-related Skills like Vercel/Cloudflare.
Read MoreOne-click Deployment of Frontend Projects to Netlify with the netlify-deploy Skill
### Translated Abstract: This article introduces the OpenAI curated skill `netlify-deploy`: it uses the Netlify CLI (`npx netlify`) to complete authentication, site association/creation, dependency installation, and preview/production deployment. It explains the installation methods in the Agent Skills directories of Cursor, Codex, Claude Code and other platforms, provides official workflow command examples, notes for `netlify.toml`, as well as usage suggestions such as sandbox networking and key management.
Read MoreSelf-improving Programming Agents Have Gone Viral: Long-term Autonomous Tasks, What Are Developers Betting On?
# 2026-08-10 GitHub Trending Leader: prime-agent by PrimeIntellect-ai The repo gained approximately 2,356 stars in a single day. Positioned as a self-improving RLM Agent oriented towards coding and long-term autonomy, this article verifies its two core abstractions based on the official repository and blog: Recursive Language Model (persistent IPython and programmatic sub-agents) and Continual Harness (small-step rewrite prompts/memory/skills via /refine with rollback capability). It explains how daemon, objectives, and bounded/autonomous modes support long-running tasks, clarifies that "self-improvement" refers to scaffolding state iteration rather than weight self-training, and also warns about the non-safe sandbox risk.
Read MoreClaude Code v2.1.224: Multiple independent sessions can send messages directly to each other, say goodbye to copy-pasting between terminals
Anthropic launched cross-session messaging in Claude Code v2.1.224 (released on August 7, 2026): independently running sessions on macOS/Linux can discover each other via ListAgents and send each other plain text summaries via SendMessage, without manually copying context between terminals. The messages do not carry conversation history or files, and the recipient still needs to approve sensitive operations on their own; the communication uses local sockets on the same machine, and cross-machine support is limited to replies via Remote Control. This article introduces the mechanism, scenarios, usage and security boundaries based on official documentation.
Read MoreClaude Code Launches Default Auto Mode on August 14: AI Programming Agents Move from "Review Line-by-Line" to Autonomous Execution
Anthropic announced that starting August 14, newly created Claude Code sessions for Pro, Max and Team users will enable Auto Mode by default, replacing one-by-one permission pop-ups with a safety classifier. Official controlled experiments show that the classifier intercepts approximately 89% of dangerous commands, far higher than the approximately 14% interception rate of manual approval; PR output for Team users increased by about 25%. This article sorts out the Auto Mode mechanism, safety data, applicable scope of each subscription plan, and developer response suggestions.
Read MoreJupyter Notebook: Official OpenAI Skill to Enable Agents to Generate Jupyter Notebooks in Compliance with Specifications
OpenAI's curated Skill jupyter-notebook targets two scenarios of experimental and tutorial Jupyter Notebooks. It generates structurally standardized .ipynb files through bundled templates and the new_notebook.py scaffolding script, and is also equipped with experiment/tutorial mode guides and quality checklists. This article verifies the official SKILL.md and repository scripts, and introduces the installation methods (Codex $skill-installer, Cursor .cursor/skills), typical commands and Agent prompts, as well as applicable scenarios and precautions.
Read Morecli-creator: Turn API Documentation into Agent-Invokable Command-Line Tools
cli-creator is a curated Skill in the OpenAI Skills repository. It guides AI to generate installable, composable command-line tools that output stable JSON from API documents, OpenAPI, curl, or SDK scaffolds, and is paired with a Companion Skill for subsequent Agent reuse. This article introduces its core command contracts (doctor/discovery/resolve/read/write), runtime selection for Rust/Node/Python, authentication priority, as well as installation and typical usage in tools such as Codex and Cursor.
Read More# Sentry Skill: Integrating Production Error Troubleshooting into AI Agent Workflows
Sentry is an Agent Skill maintained by OpenAI in the curated directory of the openai/skills repository, which enables read-only observability queries via the official Sentry CLI: listing unresolved issues, viewing event details, and calling issue explain/plan to generate root cause analysis and repair suggestions. This article introduces its positioning, core commands, installation methods for both the CLI and the Skill (Codex's $skill-installer and Cursor's .cursor/skills), as well as precautions including the default 24-hour production environment query scope, JSON output format and security desensitization, which is suitable for DevOps/SRE to integrate online troubleshooting into AI workflows.
Read MoreLinear Skill: Let AI Agents Directly Operate Linear Tickets, Not Just Write Code
### 译文： Officially selected by OpenAI: Skill Linear, which enables Agents to read, create and update Issues, projects and team workflows via Linear MCP. This article introduces its positioning, core capabilities, installation steps for Codex/Cursor, typical usage scenarios such as Bug triage and Standup synchronization, as well as precautions including OAuth and rate limits.
Read Moreyeet: Official OpenAI Skill, Run stage → commit → push → Create PR in one sentence
yeet is a curated Agent Skill maintained by OpenAI in the openai/skills repository. It only uses the GitHub CLI to complete git add, commit, push and create or update a Pull Request in one go when the user explicitly requests it. This article verifies its workflow based on the official SKILL.md: automatically creating a branch from the default branch, perceiving PR templates, avoiding duplicate PRs, and creating new PRs as Drafts. It also explains the installation methods and typical trigger phrases in Codex and Cursor. It is suitable for GitHub developers who want to hand over the final mile of Git release to AI Agents.
Read More# migrate-to-codex: Official Migration Skill to One-Click Move Claude Code Configuration to Codex
OpenAI's official Skill `migrate-to-codex` can convert Claude Code's instructions, Skills, Hooks, MCPs and sub-Agents into Codex's standard directory structure, supports scan, plan, dry-run and verification, and outputs a migration report. This article introduces installation and activation, typical commands, as well as the complementary relationship and limitations between it and Codex /import.
Read More# Slack-GIF-Creator: Let AI Help You Make GIFs Compliant with Slack Specifications
Slack-gif-creator is an Agent Skill in Anthropic's official Skills repository. It encapsulates constraints such as GIF dimensions, frame rate and color specifically for the Slack scenario, and provides a GIFBuilder assembly tool, validators for verification, as well as guides on easing and animation concepts. This article introduces its positioning, core capabilities, as well as installation methods and typical usage in AI programming tools such as Cursor and Claude Code, helping developers quickly produce GIFs that can be uploaded to Slack using natural language.
Read MoreDetailed Explanation of canvas-design Skill: Incorporating Design Philosophy into AI to Generate PNG/PDF Static Visual Works
Canvas-design is a creative Agent Skill in Anthropic's official Skills repository. It adopts a two-step workflow of "first formulating design philosophy, then expressing it on the canvas, and finally conducting secondary refinement", and outputs .md manifesto and .png/.pdf visual finished products. This article verifies its core capabilities, canvas-fonts font resources, installation methods in Cursor and Claude Code, as well as typical usages such as posters and brand visuals and copyright considerations based on the official SKILL.md.
Read More