Tools

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.

Free, open-source offline OCR desktop app for screenshots, batch images, scanned PDFs and QR codes, callable via the umi-ocr CLI or an HTTP API (the CLI relies on the app's local HTTP service, on by default). Windows and Linux only.

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.

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.

Official Anthropic plugin that solves competition math such as IMO and Putnam problems, with adversarial checks by an independent verifier that only sees the clean proof. Gives up explicitly rather than bluffing when unsure, and outputs LaTeX/PDF once verified.

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.

Official Anthropic plugin that builds a shareable status page for big multi-track projects such as migrations, launches or research: goals, workstream order, next steps and risks; say 'refresh' to update the same link. Needs a claude.ai login; Artifacts are a beta for Team and Enterprise plans.

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.

Universal document converter between dozens of formats including Markdown, Word, HTML, LaTeX and EPUB, with templates, citations and Lua filters. PDF output uses LaTeX by default, which you install separately.

Turns common prompts such as summarizing, extracting insights and rewriting into reusable patterns you pipe text, web pages or YouTube transcripts through, using many model providers or local Ollama. Can also run as a REST API. Run fabric --setup first to configure models.

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.

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.

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.

Data engineering plugin from the wshobson/agents marketplace: a data engineer subagent, a data pipeline command, and skills for Airflow DAGs, dbt transformations, Spark tuning and data quality, to help build ETL and data warehouses.

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.

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.

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.

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.

Headless browser written from scratch in Zig for AI agents and automation, using less memory and running faster than headless Chrome in official benchmarks. fetch turns pages into Markdown, and it can serve CDP or MCP. Telemetry is on by default (an env var disables it); Windows needs WSL.

Core financial modeling plugin: builds DCF, LBO, three-statement and comps models, reviews Excel models and banking decks, and centrally configures financial data connectors. The foundation plugin of Anthropic's official financial services suite.

Official Anthropic skill for cleaning messy Excel exports: trims spaces, standardizes case and dates, converts text numbers, dedupes, and flags mixed types, garbled text and errors. Keeps originals via helper-column formulas and confirms each step. Works in Claude for Excel; local files need Python.

Builds M&A accretion/dilution models: sources and uses, pro forma EPS and goodwill amortization impact, with sensitivities on synergies, premium and cash/stock mix, in an Excel workbook. You supply share prices, EPS and deal terms. From Anthropic's investment-banking plugin; needs expert review.

Partner plugin from Kensho, part of S&P Global: uses Capital IQ data to produce one- to two-page company tearsheets as Word docs, earnings previews, and M&A deal summaries by sector or company. Needs a Capital IQ Pro or S&P LLM-ready API subscription; needs expert review.

Anthropic's official fund admin agent plugin: reads GP valuation packages, reviews each portfolio company's valuation against the template, calculates fund NAV, carried interest and LP distributions, and assembles LP reports for review. Connect your own portfolio data sources.