Tools

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.

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.

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+.

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.

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.

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.

MiniMax's official Excel skill: read, analyze, create, edit and validate xlsx files and fix broken formulas. Edits existing files at the XML level to keep formatting, formulas and pivot tables; writes results as formulas with finance-style color coding. Needs Python (pandas); LibreOffice optional.

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.

PostgreSQL command-line client with smart autocompletion and syntax highlighting. Compatible with psql environment variables, and -c runs a statement and exits, so agents can query databases non-interactively.

Simon Willison's LLM CLI and Python library: call OpenAI, Claude, Gemini and local models from the terminal, with conversations logged to SQLite automatically, plus embeddings, structured extraction, tool calling and a plugin system.

ByteDance's open-source, general software engineering agent: trae-cli edits files and runs commands from natural language, supports multiple model providers and MCP, and records full execution trajectories. Transparent design suits agent research and customization. Needs your own model API key.

MySQL terminal client with smart autocompletion and syntax highlighting, also compatible with MariaDB and TiDB. Supports --execute and batch mode with CSV or table output, so agents can run SQL directly.

Connects to the Arize Phoenix observability platform so agents can query LLM traces and sessions, manage prompts, browse datasets and read experiment evaluation results. Maintained by Arize; needs a self-hosted or cloud Phoenix instance.

Publishes SQLite databases as browsable, queryable web pages and JSON APIs, with SQL queries, metadata and plugins, and deploys to Cloud Run and other platforms with datasette publish. Great for data exploration and data journalism. Needs Python 3.10+.

Lets agents work with the Hugging Face Hub through the hf CLI: search and download models and datasets, manage repos and Spaces, and run training and evaluation jobs on cloud GPUs, with more workflow skills installable as needed. Maintained by Hugging Face.

Lets agents fine-tune language and vision models with TRL or Unsloth on Hugging Face Jobs cloud GPUs, supporting SFT, DPO, GRPO and reward models, and convert results to GGUF for local use. Requires an HF Pro or higher paid plan. Maintained by Hugging Face.

Hugging Face's official skills: manage Hub models and datasets with the hf CLI, fine-tune language and vision models, run model evaluations, and build Gradio apps deployed to Spaces. Needs an HF account; cloud training on HF Jobs requires a paid plan.

Teaches agents the Hugging Face Hub CLI hf: search and download models, manage datasets, Spaces, Buckets and repos, and run Jobs and inference endpoints. The skill content is generated from your local CLI, so install hf first. Maintained by Hugging Face.

The official MCP debugging tool: connect to any MCP server through a web UI, CLI or terminal UI to list and call its tools, resources and prompts. CLI mode outputs JSON, suited to scripts and CI smoke tests.

Reads the exact position of every character, line and table cell in digital PDFs: the CLI exports layout-preserving text or CSV/JSON details, and the Python API extracts tables and form fields, ideal for invoices, statements and reports. Runs locally with Python; scans need OCR first.

Universal psql-style SQL command line: one tool to connect to PostgreSQL, MySQL, SQLite, SQL Server, Oracle and dozens of other SQL and NoSQL databases, with support for copying data between databases.

Processes CSV, TSV, JSON and other structured data like awk, sed, cut, join and sort, but by field name, for cleaning, aggregation, format conversion and pretty-printing. The command is mlr; written in Go with no runtime dependencies.

Open-source research agent: one command runs literature reviews, deep research, paper reviews, paper-code consistency checks and replication plans, searching arXiv, PubMed and more with sources recorded. Good for grad students writing reviews. Run feynman setup to sign in to a model provider.

Linter and formatter for 20+ SQL dialects that auto-fixes most issues and handles Jinja templating and dbt projects (dbt needs a plugin), suited to warehouse code review and CI.