Herramientas

Self-improving agent from Nous Research with built-in memory and a learning loop that turns experience into skills. Works with any model provider; the hermes command has a terminal UI, and a gateway connects it to Telegram, Slack and more and runs scheduled tasks.

High-throughput LLM inference and serving engine: vllm serve starts an OpenAI- and Anthropic-compatible server in one command. Supports 200+ model architectures from Hugging Face, quantization and distributed inference. Aimed mainly at NVIDIA, AMD and other GPUs.

Generates natively editable PPTX from PDFs, Word files, web pages and other sources, with native shapes, data charts and master layouts. Can also fill your own template and add animations and narration to finished decks. Needs Python 3.10+ and its dependencies.

MuseScore 4 command-line wrapper from CLI-Anything: lets agents transpose scores, extract parts, add or remove instruments, inspect score info and export PDF, MIDI, MusicXML, MP3 or braille. Handy for music teachers preparing scores in bulk. Needs MuseScore 4 and Python 3.10+.

Engine for math and explainer animations in Python (Community Edition, ManimCE): write scenes and render them to video with the manim command, letting agents create teaching and science animations. On macOS install cairo and pkg-config first; formulas need LaTeX.

Distills technical books, doc folders or paper collections (PDF, EPUB, DOCX, Markdown and more) into an agent skill with a core framework, on-demand chapter files, glossary and cheat sheet for lookup while working. Extraction needs local Python; poppler or docling optional for PDFs.

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.

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+.

Multi-language git hook manager: declare formatting, lint, secret scanning and other hooks in .pre-commit-config.yaml to run automatically before each commit, or have the agent self-check with pre-commit run --all-files before committing.

Converts text to speech with Microsoft Edge's online TTS service and can generate subtitle files at the same time. No API key needed, with voices for many languages. Not an official Microsoft project and depends on that online service staying available.

Bundles 60+ full-stack specialist skills into one plugin: experts for 12 languages including Python, TypeScript, Go, Rust and Java, and frameworks like React, Django and Spring Boot, activated automatically by request. Also includes Jira and Confluence workflow commands (needs Atlassian MCP).

PDF translation CLI for research papers that preserves formulas and layout as much as possible, producing bilingual side-by-side or translation-only PDFs. Needs an OpenAI-compatible API (local Ollama works too); currently focused on English to Chinese.

Converts the output of 100+ commands such as dig, ps, ls and ifconfig, plus common file formats, into JSON so agents can parse it reliably with jq or scripts. Also usable as a Python library.

Offline speech toolkit for Apple Silicon Macs: CLI text-to-speech (including Chinese and voice cloning) and speech-to-text, for voicing lessons and explainer videos or transcribing lectures and interviews, with data staying local. Needs an M-series Mac and Python 3.10+; MP3 export needs ffmpeg.

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.

Lets agents operate Home Assistant: control devices, query state and history, create and debug automations and edit dashboards, with 80+ tools. Community-maintained (unofficial); requires your own Home Assistant instance, and running via uvx needs a long-lived access token.

Moves files to the trash instead of deleting them, with commands to list, restore and empty trashed files, so anything an agent deletes by mistake can be recovered. Follows the FreeDesktop.org trash spec and shares the trash with GNOME and KDE.

Knownsec's open-source Python-use agent: describe a task in plain language and it writes and runs Python on your machine, e.g. tidying Excel files, summarizing attendance or screening resumes. Needs Python 3.11+ and a model API key such as DeepSeek; code runs locally, so back up important files.

Converts PDFs to editable Word files, keeping paragraphs, tables, images and layout as closely as possible, and can extract tables alone, handy when a contract or exam only exists as PDF. Needs Python; digital PDFs only, OCR scans first. No longer actively maintained by Artifex.

Recognizes images or whole PDFs (including scans) with math formulas and tables into Markdown and LaTeX, strong on English and Chinese and supporting 80+ languages, handy for digitizing exams, lecture notes and study notes. An open-source Mathpix alternative that runs locally with Python.

Unified search across 20+ academic sources including arXiv, PubMed, bioRxiv, Semantic Scholar and OpenAlex, returning deduplicated, normalized results and downloading full text via open-access channels first. Most sources need no API key.

A three-stage workflow for math modeling contests like MCM/ICM and CUMCM: analysis, solving and plotting in Python or MATLAB, and a Word (optionally LaTeX) paper, with stage-check subagents and OpenAlex plus AnySearch literature search. Generated papers are for reference only.

Command-line reference and bibliography manager: add papers by DOI with metadata fetched automatically, search by author, title or tag, and import or export BibTeX. Each entry is a readable YAML file that agents can read and write easily; a web UI is included. Needs Python.

Jupyter's official tool for notebook assignments: once teachers mark up questions and solutions, the CLI generates student versions, collects submissions, auto-grades and produces feedback. Suits programming and data courses. Needs Python and Jupyter; assignments must use nbgrader's markup.