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Official Lark (Feishu) skill: view and search events, create or edit meetings and invite attendees, check colleagues' availability and suggest free slots, and book meeting rooms. Needs lark-cli on a machine with Node.js, plus app setup and authorization.

Official Lark (Feishu) skill to read, create and edit Lark docs and wiki pages, insert or download images and attachments, and work with whiteboards and mind notes. Depends on lark-cli and the lark-shared skill; requires Lark authorization.

Official Lark (Feishu) OKR skill: view OKR cycles, create and edit objectives and key results, update quantitative progress and notes, and adjust alignment, order and weights to drive team goals (no performance reviews). Needs lark-cli and authorization.

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: create and assign tasks, set due dates and reminders, add subtasks, organize task lists, comment and mark tasks done, helping project managers and admins track team work. Needs lark-cli with app setup and authorization; install together with lark-shared.

Official Lark (Feishu) approval skill: list pending, handled and submitted approvals; approve, reject, transfer, return, remind or withdraw; and find and submit native approvals such as leave or expense requests. Needs lark-cli with app setup and sign-in authorization.

The 20+ skills that ship with the official Lark (Feishu) lark-cli, covering messages, docs, Base, Sheets, calendar, mail, tasks, approvals and meeting notes. Install lark-cli and complete app setup and authorization first.

Official Lark (Feishu) CLI with 200+ commands for messages, docs, Base, Sheets, calendar, mail, approvals, OKRs, meetings and Minutes, plus 20+ bundled lark-* agent skills and structured output. Create a Lark app and sign in first.

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+.

Semantic multi-language static analysis: find vulnerabilities and bugs with rules that look like source code, across 30+ languages with custom rules. Scans locally by default without uploading code; cross-file analysis and Pro rules require sign-in.

Semgrep's official MCP server, now part of the main semgrep repo and started with semgrep mcp: lets agents run static security scans, find issues with custom rules and inspect syntax trees. Requires the Semgrep CLI; connecting to the AppSec platform needs SEMGREP_APP_TOKEN.

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.

Turns an Obsidian vault into a local-first knowledge base: imports sources into interlinked notes with citations, answers questions from what is already in the vault, and adds 15 skills including search, vault health checks and Canvas knowledge graphs.

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.

Bundles a whole web page with its CSS, images, fonts and scripts into a single HTML file that opens offline exactly as it looked, good for archiving pages or handing them to an agent for offline analysis. It does not run JavaScript, so pre-render dynamic pages with a headless browser.

Open-source zero-shot TTS via f5-tts_infer-cli: from a few seconds of reference audio it reads Chinese or English text in the same voice, handy for lessons and videos. Needs Python, PyTorch and FFmpeg, ideally a GPU. Pretrained models are non-commercial; get consent before cloning a voice.

Writes precise prompts for a specific AI tool: identifies the target tool, extracts your intent, asks at most three questions if details are missing, then outputs a lean, paste-ready prompt. Covers dozens of tools including ChatGPT, Claude Code, Cursor, Midjourney and Sora.

Turns 18 kinds of sources, including doc sites, GitHub repos, PDFs and videos, into skill packages for Claude and other platforms, or exports RAG chunks and vector store data. Optional MCP server, and it can call a local agent like Claude Code to enrich content. Needs Python 3.10+.

Open-source grammar, spelling and style checker for 20+ languages including English, German, French, Spanish and Portuguese. Proofread drafts in bulk from the CLI or run a local HTTP checking server for agents. For writers, translators and language teachers. Needs Java 17 (Homebrew includes it).

Security baseline and compliance checks for AWS, Azure, GCP, Kubernetes, GitHub, M365 and more, with built-in CIS, NIST, PCI-DSS, SOC 2 and other frameworks. Generates reports or opens a local dashboard. Configure credentials for each cloud account first.

Plugin marketplace for AI research with nearly 100 skills in 23 categories, from ideation, fine-tuning and post-training to distributed training, inference serving, evaluation and paper writing, coordinated end to end by the autoresearch skill.

Nearly 100 skills spanning the AI research workflow: ideation and literature review, fine-tuning and post-training, distributed training, inference serving, evaluation, interpretability and paper writing, tied together by an autoresearch orchestration skill.

Command-line framework for warehouse modeling and ELT transformations: write models in SQL and let dbt handle dependencies, data tests and documentation. v2 is rewritten in Rust as a single binary. Maintained by dbt Labs; needs a data warehouse connection.