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High-accuracy retrieval-augmented Q&A over paper PDFs, text and Office documents, filling in citation metadata, checking retractions and attaching traceable sources to answers. Provides the pqa CLI and a Python library. Needs an LLM API key by default; local models can be configured.

Terminal tool for exploring and wrangling tabular data: opens dozens of formats including CSV, JSON, Excel and SQLite for filtering, sorting, pivots and frequency counts. --batch mode replays actions headlessly or converts file formats.

Publication-quality matplotlib plotting skill from a Yale PhD student: bar charts, trends, heatmaps and multi-panel figures with consistent fonts, colors and export settings, plus real plotting scripts from papers published in venues like Nature Machine Intelligence. Needs Python.

Say build a harness for this project and it designs a domain-specific agent team, generating subagent definitions, companion skills and orchestration, validates them and keeps evolving them from feedback. Supports workflow orchestration, persistent agent teams and subagent delegation.

Manage database schemas as code: declare the desired schema in SQL, HCL or your ORM and Atlas plans, lints and applies migrations, and can export existing databases as HCL, SQL or Mermaid ER diagrams. Supports PostgreSQL, MySQL and a dozen other databases.

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.

Query, modify and convert JSON, YAML, TOML, XML, CSV, HCL, INI and more with one selector syntax, editing config files in place or converting between formats, handy for agents handling structured data in scripts. A single dependency-free binary that works much like jq or yq.

Query cloud resources and SaaS APIs live with SQL: plugins map AWS, Azure, GCP, GitHub, Kubernetes and other services to tables you can select from directly, no ETL needed. A single binary with Postgres built in.

Turns Peng Sida's public research-writing notes into a skill: revises abstracts, introductions, methods and experiments of ML/CV/NLP papers from a reviewer's view, checks that each claim has experimental evidence, and runs a pre-submission self-check. Pure methodology, no API key.

Trail of Bits plugin for Culture Index assessments: profiles individual traits, checks team balance (gas, brake, glue), compares people with job profiles to flag burnout and attrition risk, and helps draft hiring profiles. Needs your own reports (JSON or PDF); PDFs need uv.

Diffusion model inference in pure C/C++: one sd-cli command runs SD, FLUX, Qwen Image, Wan and more locally to create or edit images and short videos, with Metal acceleration on Mac. No cloud needed; bring your own model weights and use a release binary or build from source.

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.

OpenAI's official Codex plugin with 18 skills to choose, design, build, test and export web charts, maps, dashboards, Gantt charts and UML, using D3, Vega-Lite and Three.js with attention to accessibility and responsiveness. Codex only.

OpenAI's official Codex plugin for SharePoint: summarizes organization sites, pages and files, finds document owners and status, and plans updates to documents, spreadsheets or decks. Requires Codex with a ChatGPT sign-in and a work Microsoft 365 account.

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.

Build with OpenAI best practices inside Codex: call the OpenAI API, build and deploy agents with the Agents SDK, create ChatGPT apps and prepare submission materials, and create API keys directly. Maintained by OpenAI; Codex only.

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 Codex plugin for answering product and business questions with data: metric anomaly diagnosis, KPI design, market sizing, dashboards and reports, notebooks and data quality checks. Connects to data warehouses and BI 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.

OpenAI's official set of 18 web data visualization skills: chart selection and critique, D3, Canvas, Three.js, maps, statistical uncertainty, live dashboards, Gantt charts, UML and scrollytelling. Ships with a Codex plugin; installed alone, the plugin-level references are missing.

OpenAI's official Codex plugin that guides sequencing analysis from BCL/FASTQ: QC, RNA-seq differential expression, single-cell, variant calling and metagenomics, favoring nf-core and other public pipelines with reproducible run logs. Checks for local tools first. Research use only.

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.

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.