Tools

Google's official skill library, focused on Google Cloud: 100+ skills for gcloud, Cloud Run, GKE, BigQuery, IAM, monitoring and logging, and the Well-Architected Framework, plus Ads and Analytics.

From Firecrawl: converts Word, PowerPoint, Excel, PDF, EPUB, RTF and more into clean Markdown locally in milliseconds, keeping headings, tables, footnotes and formulas so agents can read attachments. Needs Node.js; optional Firecrawl cloud OCR for scans uploads the whole file.

Offline speech transcription and translation based on Whisper; audio never leaves your machine. buzz add exports lectures, interviews and meeting recordings to TXT, SRT or VTT. pip install needs Python 3.12 and FFmpeg; a desktop app is also available. Check transcripts manually.

Compiles Markdown chapters into an online book with a table of contents, full-text search and themes, good for manuals, lecture notes and course material; agents can edit chapter files and rebuild to preview. Maintained by the Rust team; install a prebuilt binary or via cargo.

Industrial-grade open-source speech recognition toolkit from Alibaba's ModelScope, with an agent-friendly funasr command that turns audio into text, JSON or SRT subtitles in one step, with speaker diarization and timestamps. Strong on Chinese. Requires PyTorch.

Unofficial Python library and CLI for driving Google NotebookLM (now Gemini Notebook): bulk-import sources, ask cited questions, and generate and download podcasts, videos, slides, quizzes and flashcards. Ships an agent skill. Relies on undocumented APIs and needs a Google sign-in.

AI2's tool for converting PDFs and scans to Markdown with a vision LLM, handling equations, tables, handwriting and multi-column layouts, suited to bulk digitizing papers and archives. Local runs need an NVIDIA GPU with 12GB+ VRAM; otherwise use a paid OpenAI-compatible remote endpoint.

Style and convention linter for Swift, with most rules built on SwiftSyntax. Configure it with .swiftlint.yml, auto-correct with --fix, and run it in an Xcode build phase or as a SwiftPM plugin.

Lets Claude Code push ML research forward unattended: literature review, topic selection, experiment deployment, cross-model review loops and paper writing through rebuttal, in 80+ skills. Codex acts as the independent reviewer by default; other model pairings work too.

Browser control from the browser-use team: an editable CDP connection lets agents drive the Chrome you are already using, writing missing helper functions as they go and keeping them for reuse. Also offers an MCP server. Allow remote debugging in Chrome on first use.

Context and harness engineering skills: context fundamentals, degradation diagnosis and compression, multi-agent architectures, memory systems, tool design, LLM-as-judge evaluation and self-improvement loops. Focused on principles and design patterns, not tied to any agent platform.

Context and harness engineering skills covering context compression and optimization, multi-agent architectures, memory systems, tool design and LLM-as-judge evaluation, activated automatically by task. Aimed at building production-grade agent systems.

Official Lark (Feishu) skill to create and edit Lark Sheets: formulas, charts and pivot tables, conditional formatting and filters, plus import and export of local Excel/CSV, for summaries, budgets and reports. Needs lark-cli on a machine with Node.js, plus app setup and authorization.

Official Lark (Feishu) skill for Lark Base: create tables, add fields, add and edit records, build views, forms and dashboards, or apply ready-made templates, good for sign-ups, asset registers and trackers. Needs lark-cli on a machine with Node.js, plus app setup and authorization.

Write your resume in YAML and render a cleanly typeset PDF from the command line: multiple themes, fine control of margins, colors and fonts, strict field validation and multi-language support. A companion agent skill is available. Needs Python 3.12+.

Automattic's offline English grammar checker: checks spelling, grammar and word choice locally in milliseconds without sending your text anywhere. Homebrew installs harper-cli for batch-checking files (still experimental) and harper-ls for editors. English only.

Alibaba's open-source offline data sync tool: JSON job configs batch-sync between heterogeneous sources like MySQL, Oracle, PostgreSQL, Hive, HDFS and MaxCompute, run with python datax.py. Needs JDK 1.8+ and Python; download and unpack the official toolkit.

CLI version of the VideoCaptioner subtitle assistant: transcribes courses, lectures and interviews, uses an LLM to segment, proofread and translate, then burns subtitles into the video. Free ASR and Bing translation work out of the box; LLM refinement needs an API key. Python 3.10 to 3.12.

Write end-to-end UI tests for Android, iOS and web apps in YAML. The CLI includes an MCP server (maestro mcp) so coding agents can tap, assert and generate tests on simulators. Requires Java 17+.

MCP built into the CLI of the Maestro mobile UI testing framework (maestro mcp): lets agents view the screen, tap, scroll and assert on iOS/Android simulators, Android devices or Chromium, and write and run YAML end-to-end flows. Needs the Maestro CLI and Java 17+. Official.

Simplifies Figma designs into layout and style data for coding agents, so UIs built from the design are more accurate than working from screenshots. Requires a Figma personal access token.

Lets agents call thousands of ready-made scrapers and automation Actors from Apify Store to pull data from social media, search engines, maps, e-commerce sites and more. Maintained by Apify; needs an Apify account (OAuth) or API token.

ModelScope's official training framework for LLMs and multimodal models: the swift command covers pretraining, fine-tuning, RL, inference, evaluation, quantization and deployment for 600+ text and 400+ multimodal models, with Megatron parallelism and a web UI. Usually needs a GPU.

Version datasets and models the way Git versions code: data lives in remote storage like S3 or GCS while versions are tracked in your Git repo. Also offers reproducible pipelines and local experiment tracking, rerunning only the steps affected by a change.