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From HKU's Data Intelligence Lab: plugins or skills for Claude Code, Codex and other agents generate agent-callable CLIs for apps like GIMP, Blender and LibreOffice, and the cli-hub package manager finds and installs ready-made community CLIs. Needs Python 3.10+.

Open-source crypto trading framework: download market data, backtest and optimize strategies, and paper trade from the CLI while agents iterate on strategies. Docker recommended; strategies need Python and live trading needs exchange API keys. Backtests don't guarantee returns.

General-purpose AI agent that runs on your machine, with a desktop app, CLI and API. Written in Rust, works with 15+ model providers and connects to 70+ extensions via MCP. Originally from Block, now part of the Linux Foundation's AAIF.

Teaches agents standard single-cell RNA-seq analysis with Scanpy: QC, normalization, PCA/UMAP, clustering, differential expression and plots, with ready-to-run pipeline scripts and guidance on converting Seurat and other R objects to h5ad. Needs Python 3.12+; by K-Dense.

Unified database lookup skill from K-Dense's scientific collection: reproducibly queries about 80 public database APIs such as PubChem, UniProt, ChEMBL, ClinicalTrials.gov and FRED, returning traceable results with endpoints, parameters and count checks. Some need API keys.

C/C++ port of OpenAI's Whisper speech recognition model that transcribes audio offline and outputs subtitles. Runs on CPU, with Apple Silicon and various GPU acceleration. Download a ggml-format model first.

Guides agents to the right statistical method for research data: t-tests, ANOVA, chi-square, regression and Bayesian analysis, checking assumptions, computing effect sizes and power, and reporting results in APA format. Python-based (pingouin, statsmodels); by K-Dense.

Astral's extremely fast Python linter and formatter written in Rust, replacing Flake8, isort and Black, with 900+ built-in rules and auto-fix.

Terminal multiplexer: run multiple sessions and panes in one terminal, with processes surviving disconnects. Agents use it to host long-running tasks and drive interactive programs, and many parallel multi-agent session tools build on it.

Microsoft's open-source AI quant investment research platform: the qrun command runs dataset building, model training, backtesting and evaluation from a YAML config, with many benchmark models. The official dataset is paused, so prepare market data per the README first.

Official Anthropic plugin that reads local session logs in ~/.claude/projects and generates an interactive HTML usage report covering tokens, cache hit rate, subagents, skills and the most expensive prompts, with optimization tips. Needs Node.js.

Connects Claude Code to the Pyright language server for static type checking and code intelligence in Python. Install pyright first with npm, pip or pipx. Official Anthropic plugin.

Creates or improves Agent Skills from scratch: writes eval cases to test them, runs benchmarks with variance analysis, and tunes descriptions for more accurate triggering. Maintained by Anthropic.

Designs and builds MCP servers: first picks a deployment model among remote HTTP, MCPB bundles and local stdio, then guides tool design, auth and in-chat interactive components. Maintained by Anthropic.

Lightweight multi-protocol command-line downloader that fetches in parallel segments from multiple sources over HTTP(S), FTP, SFTP, BitTorrent and Metalink. Resumes downloads, reads URLs in bulk from text files and offers a JSON-RPC interface for scripts or agents.

Quant trading plugin from the wshobson/agents marketplace: quant analyst and risk manager subagents plus backtesting and risk metrics skills for strategy backtests, portfolio optimization and risk measures like VaR, Sharpe ratio and max drawdown. Needs local Python; not investment advice.

Plans teams for seed to Series A startups: which roles to hire at each stage and in what order, org structure, plus salary, equity ranges and headcount budget. Compensation benchmarks are 2024 US market data; adjust for your market and have finance and legal review the plan.

Plugin for building LLM apps: LangGraph agents with memory and tool use, hybrid-search RAG, vector index tuning, prompt optimization and LLM evaluation. Includes 3 subagents and 8 skills.

Business analytics plugin from the wshobson/agents marketplace: KPI dashboard design and data storytelling skills plus a business analyst subagent to choose metrics, plan dashboard layouts and turn data into reports executives or investors understand. Methods and templates only; no data connections.

MLOps plugin from the wshobson/agents marketplace: data scientist, ML engineer and MLOps engineer subagents and a /ml-pipeline command that runs the pipeline in phases from data analysis and training to deployment and monitoring, plus ML pipeline and recommender system skills.

Anthropic's official finance agent plugin for fund accounting: reconciles the general ledger and subledger by trade date, lists breaks, traces causes and builds an exception report for sign-off without posting. Runs in Claude Code or Cowork; connect your own GL and subledger data via MCP.

Anthropic's official finance agent plugin: runs month-end close for an entity and period, producing accrual details and draft journal entries, roll-forward reconciliations and P&L and balance sheet variance commentary, packaged for controller approval without posting. Needs a GL data source.

Official Anthropic finance skill that checks Excel for formula errors like #REF!, numbers hardcoded in formulas, sum ranges that miss rows and mixed units; on full models it also checks the balance sheet balances and cash ties. Lists issues and fixes and asks before changing anything.

Builds a DCF valuation in Excel: pulls figures from SEC filings and research, projects free cash flow, computes WACC and terminal value, and adds sensitivity tables. Derived values are formulas, inputs cite sources, and each step is confirmed with you. From Anthropic's financial-analysis plugin.