Инструменты

Build with OpenAI best practices inside Codex: call the OpenAI API, build and deploy agents with the Agents SDK, create ChatGPT apps and prepare submission materials, and create API keys directly. Maintained by OpenAI; Codex only.

OpenAI's official set of 18 web data visualization skills: chart selection and critique, D3, Canvas, Three.js, maps, statistical uncertainty, live dashboards, Gantt charts, UML and scrollytelling. Ships with a Codex plugin; installed alone, the plugin-level references are missing.

OpenAI's official Codex plugin that guides sequencing analysis from BCL/FASTQ: QC, RNA-seq differential expression, single-cell, variant calling and metagenomics, favoring nf-core and other public pipelines with reproducible run logs. Checks for local tools first. Research use only.

Creates, edits and validates reproducible Python and SQL Jupyter notebooks: organizes cells as reports or tutorials, checks conclusions against actual output and reruns top to bottom before handoff. Maintained by OpenAI in the Data Analytics plugin of openai/plugins.

OpenAI's official Codex plugin with 18 skills to choose, design, build, test and export web charts, maps, dashboards, Gantt charts and UML, using D3, Vega-Lite and Three.js with attention to accessibility and responsiveness. Codex only.

MagicPath's official Codex plugin from OpenAI's plugin marketplace: search and install UI components from MagicPath canvases, apply team themes, and move interfaces from local code onto the canvas to keep iterating. Needs a MagicPath account and Node.js.

OpenAI's official life-science skills: 49 skills query public databases such as UniProt, ClinVar, gnomAD and AlphaFold through Python scripts, with a router skill that breaks down questions, normalizes entities and compiles sourced evidence. Written mainly for Codex.

OpenAI's official data analytics skills: data quality assessment, KPI design, metric anomaly diagnosis, dashboards and analysis reports, market sizing and notebooks. Ships with a Codex plugin; some skills depend on its runtime.

OpenAI's official Codex plugin for answering product and business questions with data: metric anomaly diagnosis, KPI design, market sizing, dashboards and reports, notebooks and data quality checks. Connects to data warehouses and BI tools.

OpenAI's official Codex plugin that starts from a brief, product shots or references to generate marketing concepts, mood boards, product scenes, ad directions and social assets, compared and iterated on a reviewable board. Works with Figma and Canva.

Manage Kubernetes clusters in natural language: translates intent into kubectl operations and runs them, and can serve as an MCP server for other agents. Uses Gemini by default (API key required) and also supports OpenAI and local models. Maintained by Google Cloud.

Open-source LLM evaluation platform: one opencompass command picks the model and datasets and runs the evaluation across hundreds of benchmarks. Works with local Hugging Face models and API models, with vLLM and LMDeploy for faster inference.

Turns a theme, a line, an article or photos into a minimal, whitespace-heavy indie-zine portrait poster, and can distill reusable style rules and prompts from reference images, with built-in quality checks. Needs host image generation (e.g. Codex); otherwise outputs prompts only.

Converts raster images like JPG and PNG to SVG, handling color tracing, black-and-white line art and unevenly lit scans, for vectorizing logos, illustrations and old drawings. The CLI is a 1.0 preview installed with cargo (needs Rust); a desktop app is also available.

A more intuitive find-and-replace tool than sed: uses JavaScript/Python-style regex syntax, supports literal string mode and in-place file edits, which suits agents doing bulk text rewrites.

Converts and two-way syncs Jupyter notebooks with plain Python scripts or Markdown, so agents can edit research and teaching notebooks like ordinary text and diffs stay readable. Needs a local Python environment; install with pip.

Designs or rewrites a single-offer, high-converting landing page for SaaS, apps or services: gathers the primary action, audience, objections and proof, then lays out hero, argument and objection-handling sections with copy templates and SEO/AEO notes.

Guides the agent to build a coherent, product-grade web motion system in the style of Stripe, Linear, Apple and Vercel: reusable primitives, duration and easing defaults, stagger choreography, scroll and hover patterns, performance rules and reduced-motion support.

Gives the agent three exact Tailwind arbitrary-value shadow utilities (sm, md, lg) for layered, neutral elevation on cards, controls, popovers and hero media, with rules against mixing them with default shadows, tinting or stacking.

General guidance for building UI with Tailwind CSS: responsive and state variants, dark mode, sparing arbitrary values, components before @apply, and pitfalls such as dynamically built class names missing in production, with button and hero examples.

Builds or debugs interactive 3D web scenes with Three.js: scene, camera, renderer, lights, materials, GLTF loading and controls, plus performance basics like capping pixel ratio, handling resize, disposing WebGL resources and reduced motion.

Steers WebGL-heavy landing pages toward a chosen look by picking one of four visual lanes per page type, passing message, performance, accessibility and reliability gates, and outputting a lane, visual spec, stack, fallback and build order.

Has the agent use Iconify Simple Icons brand marks instead of typed company names in logo rows, integration grids and partner lists, sized in a 64x64 box, monochrome by default, grid-aligned and labeled for accessibility when needed.

Implements 2D physics interactions with Matter.js: a minimal Engine, Render and Runner setup with bodies, optional mouse drag constraints and SPA cleanup steps, asking about canvas size and renderer when specs are missing.