Quant Garage.Pro research.No terminal.
Analyst-grade market research used to live behind expensive professional terminals. Now it runs in your Claude, or a Python notebook, grounded in live data and silent when the numbers won’t support a take.
Thirteen one-command workflows chain multiple tools into a single market briefing. One prompt returns the regime, the risk, the upcoming earnings, the macro calendar, and the sector rotation. The read a research analyst would put together at 8am, computed on demand.
Trade like a pro. Without the terminal.
The full research desk, one prompt away.
Forty-two tools that each answer one analyst question well. Earnings previews. Risk reports. Factor research. Options flow. Corporate actions. Macro calendars. Thirteen workflows chain them into complete briefings, so one prompt returns the whole read.
Every figure carries the endpoint and timestamp it came from. Every take shows its work. Ask from Claude, import into a Python notebook, or wire it into a cron job. Same computation, same audit trail, same answer.
LLM and agent developers.
Every tool returns JSON matching a schema. Drop it into your tool-use loop and the model gets structured research instead of hallucinated finance. Ships as Claude Code skills; works with any tool-use LLM.
Traders who work in Claude.
Ask what you'd ask a colleague. "Preview NVDA earnings." "Should I trim ALLO?" The skill loads whenever the conversation touches markets. Sell-side output up top, cite trail underneath every take.
Investors with a real book.
$50K to a few million. No Bloomberg, no time to babysit a spreadsheet. Get sell-side-quality briefings on the names you actually hold: morning brief, earnings preview, portfolio review.
Developers building on Massive.
Reference implementation for the Massive API. Retry logic, fallback chains, timezone handling, audit-trail format. Read the source or fork it and ship your own.
Prompt an analyst who reads your book.
The skills load automatically whenever the conversation touches markets. No slash commands, no invocation grammar. Ask what you’d ask an analyst on your desk. Claude routes to the right tool, pulls the numbers, and writes the note.
# Cell 1 — the same tool Claude calls, imported.from quant_garage.portfolio_review import runreport = run(book_csv="book.csv")print(report["headline"])# regime: risk_on (VIX 14th pct, breadth 9/11)# variance top: ALLO 66% ⚠ flag# next earnings: NVDA Thu 4:20p ET# next macro: FOMC Wed 2:00p ET
Or skip Claude. Call the same function in Python.
Every skill is an importable Python function that returns JSON. Same client, same audit trail, same fallback chain as the Claude path. Drop it wherever you already write code.
Start with a workflow. Get the whole read in one call.
Each one picks the right tools, chains them in order, and hands you back a single briefing. Point it at your watchlist or a single ticker.
The building blocks. Compose your own workflow.
Each is a standalone run() → dict with the same client, timezone handling, audit-trail format, and significance thresholds.
The quant methods most investors haven’t seen.
A handful of these tools implement published academic research from 2007 to 2025 that individual investors have never had access to. Four worth calling out.
Every take is computed. Every number cites its call.
The whole difference between a research tool and a chatbot with a market-data plugin is that these tools refuse to fabricate when the data isn’t there. They surface the endpoint and timestamp for each figure so you can retrace the reasoning.
LLMs and agents work better on top of this surface than under it. Humans read a briefing, agents read a schema, both anchored to the same live citation trail.
You need a Massive API key. Free works for most of it.
Every install needs a key. The Basic tier is free and runs 21 tools plus most workflows end to end. Stocks Starter at $29/month opens 39 of 42 tools and every workflow. Add-ons matter only for options data, live streaming, and Benzinga fundamentals.
Two ways to install. One key.
Grab a Massive key first. Then install the Python package, the Claude Code plugin, or both. Same functions, same audit trail, same JSON, whichever way you call them.
- Works in a Jupyter notebook, a Slack bot, or a cron job
- Same code from Python, Claude Code, or any tool-use LLM
- SEC EDGAR fallback for earnings when Benzinga isn't wired
# 1. Get a Massive API key (free tier works)# massive.com/pricing$export MASSIVE_API_KEY=your_key_here# 2a. Use it from Python$pip install quant-garage$python -m quant_garage.portfolio_review book.csv# 2b. Or install the Claude Code plugin$claude plugin marketplace add https://github.com/rgourley/quant-garage$/plugin install quant-garage# Then ask Claude in plain language>review my book and flag anything I should look at>preview NVDA earnings>what's the tape doing?