Tools

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.

Figma's Codex plugin in OpenAI's official marketplace: implements UI from designs, generates Code Connect mappings, and creates or updates pages, component libraries, FigJam diagrams and slides in Figma. Needs a connected Figma account.

Reproduces issues on the Android emulator: installs builds, drives the UI with adb, dumps the UI tree, takes screenshots, captures logcat, and gathers performance evidence with Simpleperf and Perfetto. OpenAI's official Codex plugin; needs the Android SDK.

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 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 iOS skills: SwiftUI patterns and view refactoring, iOS 26 Liquid Glass, App Intents, performance audits with ETTrace sampling, memory leak hunting with memgraph, and simulator debugging. Needs macOS and Xcode; debugging skills rely on XcodeBuildMCP.

OpenAI's official Codex plugin for macOS apps: building and running, SwiftUI scenes and AppKit interop, testing and troubleshooting, signing, notarization and packaging, and logging instrumentation. Requires macOS and Xcode; Codex only.

OpenAI's official Codex plugin for iOS: SwiftUI UI work and refactoring, App Intents, simulator debugging, performance profiling and memory leak hunting, with XcodeBuildMCP built in. Requires macOS and Xcode; Codex only.

OpenAI's official Codex plugin with about 50 skills that route questions to genetics, omics, pathway, protein structure, chemistry and clinical evidence sources, can split the work across parallel subagents, and synthesize sourced conclusions.

Scrapes web pages into Markdown or structured data, with full-site crawling, sitemaps, web search and interaction with dynamic pages. Maintained by Firecrawl; the cloud needs an API key (self-hosting is possible), and the keyless hosted endpoint only offers scrape, search and parse.

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.

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.

Cleans a LaTeX project before arXiv submission: removes comments, auxiliary files and unused .tex files and images, and can compress images, so internal notes are not published with the source. From Google Research; installable with Homebrew on macOS.

Python library and CLI for extracting main web content: fetches pages, crawls via sitemaps and RSS feeds, strips headers, footers and other noise, and outputs TXT, Markdown, JSON, XML and more with metadata. Also processes downloaded HTML offline.

Anthropic's official OS-level sandbox CLI: restricts file and network access for agents, MCP servers and any command without containers, using sandbox-exec on macOS and bubblewrap on Linux. Currently a research preview.

Generates template-driven charts as single-file HTML: picks a chart from real Lupi, Basics, Glance, Maps and Interactive gallery implementations based on data shape, or fills one of 12 Chinese and English report templates. Defaults to Mono grayscale with semantic color presets. Written in Chinese.

Lets agents build, run, test and debug iOS and macOS projects and control simulators and physical devices, with a CLI mode too. Formerly XcodeBuildMCP, now maintained by Sentry; macOS only, requires Xcode 16 or later.

SwiftUI skill by Paul Hudson of Hacking with Swift: reviews and improves SwiftUI code, covering modern vs deprecated APIs, performance, navigation and layout, state management and VoiceOver accessibility, targeting iOS 26 and Swift 6.2.

Veteran suite of CSV command-line tools: in2csv converts Excel and JSON to CSV, csvcut, csvgrep and csvsort filter and sort, csvstat computes statistics, and csvsql runs SQL directly against CSV files.

Google's official skills for building ADK agents: dev workflow, scaffolding, the ADK Python API, evaluation with LLM judges and adaptive rubrics, deployment to Agent Runtime, Cloud Run or GKE, publishing and observability. Works with agents-cli; local dev needs only an AI Studio key.

Live stock and crypto quotes in the terminal with portfolio profit and loss tracking, using Yahoo Finance and Coinbase data. The main view is an interactive dashboard; ticker print exports holdings from your config at current prices as JSON or CSV for scripts and agents.

Posit's open-source scientific and technical publishing system built on Pandoc: embed Python, R or Julia code in Markdown or Jupyter notebooks, then quarto render produces HTML, PDF, Word, slides, websites and books.

Language and toolset for double-entry bookkeeping in text files: bean-check validates the ledger, bean-format normalizes it, and Fava or beanquery handle reports and queries. Plain-text ledgers are easy for agents to generate and keep in version control.

Classic plain-text double-entry accounting CLI: entries live in a text file and it produces balance, register, budget and other reports directly, with no database or hidden state, so agents can easily read and write ledgers, reconcile and report.