technical-snapshot

Compute technical indicators from OHLCV data into structured snapshot cards.

6|1|Updated Apr 2, 2026
One-click install
npx skills add https://github.com/kouko/monkey-skills --skill technical-snapshot
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: technical-snapshot
Source: https://github.com/kouko/monkey-skills/tree/main/investing-toolkit/skills/technical-snapshot
Command: npx skills add https://github.com/kouko/monkey-skills --skill technical-snapshot

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas==2.2.3, numpy>=1.26, yfinance==0.2.54, and includes scripts (resource) components.

What problem does it solve?

Consolidates historical OHLCV price data into a single, interpretable technical indicator snapshot so traders and analysts can quickly see momentum, volatility, and trend alignment without manual calculation.

Core Features & Use Cases

  • Computes standard indicators (RSI-14, MACD 12/26/9, Bollinger Bands 20/2, ATR-14, SMA 20/50/200) from yfinance price history and returns a structured JSON card and human-readable markdown snapshot.
  • Supports multi-timeframe confirmation (daily vs weekly) to reduce false signals and produces a confirmation matrix for alignment checks.
  • Integrates with the investing-toolkit pipeline: fetch price history, run deterministic indicator calculations, and hand off the snapshot to an investing-team workflow for fundamental synthesis.
  • Use Case: quickly produce a technical snapshot for a ticker to include in an investment memo or as an input to automated screening and monitoring workflows.

Quick Start

Generate a technical snapshot for ticker AAPL using one year of daily data and return the structured indicator card.

Frequently Asked Questions about technical-snapshot

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute RSI, MACD, and Bollinger Bands from yfinance price data?▼

You can compute RSI-14, MACD 12/26/9, Bollinger Bands 20/2, ATR-14, and SMA 20/50/200 from yfinance OHLCV data to generate a structured technical indicator snapshot for investment analysis.

What is multi-timeframe confirmation for technical indicators?▼

Multi-timeframe confirmation compares daily and weekly technical indicator calculations to reduce false signals, producing a confirmation matrix for trend alignment checks before making investment decisions.

Can I process multiple tickers in batch with yfinance technical indicators?▼

Yes, the tool supports batch processing of yfinance historical price series for single-ticker or multiple tickers across daily and weekly intervals to generate structured indicator cards.

Does this tool output JSON and markdown for technical indicator snapshots?▼

The tool processes OHLCV JSON input or stdin using pandas and numpy, returning both a structured JSON card and a human-readable markdown snapshot for downstream memo handoffs.

How do I integrate technical indicators into an investment memo workflow?▼

Fetch yfinance price history, run deterministic indicator calculations, and hand off the structured technical snapshot to an investing-team workflow for fundamental synthesis and memo generation.

What are the limitations of using yfinance OHLCV data for technical analysis?▼

Calculations require sufficient historical yfinance OHLCV data points to populate long-period indicators like SMA-200, and multi-timeframe confirmation depends on the availability of both daily and weekly price series.