New: 97,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Technical Analysis

by staskh in staskh/trading_skills

Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock.

MITAuto-check passedBusiness, Finance & HR

Install Technical Analysis

skills CLI
$ npx skills add staskh/trading_skills --skill technical-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install staskh/trading_skills technical-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/staskh/trading_skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/technical-analysis .claude/skills/technical-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
technical-analysis
GitHub stars
374
Token cost
~990 tokens
SKILL.md length
329 words
Files
3 (incl. scripts)
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock.

  • User asks about technical analysis
  • SKILL.md covers Instructions, Arguments, Output and Interpretation, plus 8 more sections
  • Runs Python scripts from its folder; calls uv
  • Moving averages

What it does

Technical Analysis is an agent skill from staskh/trading_skills. Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock. Use when user asks about technical analysis, indicators, RSI, MACD, moving averages, overbought/oversold, or chart analysis.

Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/correlation.py` and `scripts/technicals.py`).

It sits in Business, Finance & HR. The repository describes itself as: Claude powered advisor system for option traders. The licence is MIT.

When your agent uses it

  • User asks about technical analysis
  • Moving averages
  • Overbought/oversold

Example prompts

  • “/technical-analysis”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit b71a74f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Technical Analysis loads about 990 tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 329 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~990

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from staskh/trading_skills at commit b71a74f, republished under its MIT licence (© staskh). 329 words, ~990 tokens.

Download SKILL.mdSave it as .claude/skills/technical-analysis/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
technical-analysis
description
Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock. Use when user asks about technical analysis, indicators, RSI, MACD, moving averages, overbought/oversold, or chart analysis.
dependencies
trading-skills

Technical Analysis

Compute technical indicators using pandas-ta. Supports multi-symbol analysis and earnings data.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

bash
uv run python scripts/technicals.py SYMBOL [--period PERIOD] [--indicators INDICATORS] [--earnings]

Arguments

  • SYMBOL - Ticker symbol or comma-separated list (e.g., AAPL or AAPL,MSFT,GOOGL)
  • --period - Historical period: 1mo, 3mo, 6mo, 1y (default: 3mo)
  • --indicators - Comma-separated list: rsi,macd,bb,sma,ema,atr,adx (default: all)
  • --earnings - Include earnings data (upcoming date + history)

Output

Single symbol returns:

  • price - Current price and recent change
  • indicators - Computed values for each indicator
  • risk_metrics - Volatility (annualized %) and Sharpe ratio
  • signals - Buy/sell signals based on indicator levels
  • earnings - Upcoming date and EPS history (if --earnings)

Multiple symbols returns:

  • results - Array of individual symbol results
Crossovers
  • indicators.macd.crossover - Most recent MACD line/signal crossover, or null:
    • direction - "up" (MACD crossed above signal = bullish) or "down" (crossed below = bearish)
    • days_ago - Trading bars since the crossover (0 = happened on the most recent bar)
  • indicators.ema.crossover - Most recent EMA9/EMA21 crossover (same shape; null if none). indicators.ema also reports ema9 and ema21 alongside ema12/ema26.

Interpretation

  • RSI > 70 = overbought, RSI < 30 = oversold
  • MACD crossover = momentum shift; crossover.days_ago of 0-5 = fresh signal
  • EMA9/21 crossover confirms short-term momentum; MACD typically leads, EMA confirms
  • Price near Bollinger Band = potential reversal
  • Golden cross (SMA20 > SMA50) = bullish
  • ADX > 25 = strong trend
  • Sharpe ratio > 1 = good risk-adjusted returns, > 2 = excellent
  • Volatility (annualized) = standard deviation of returns scaled to annual basis

Examples

bash
# Single symbol with all indicators
uv run python scripts/technicals.py AAPL

# Multiple symbols
uv run python scripts/technicals.py AAPL,MSFT,GOOGL

# With earnings data
uv run python scripts/technicals.py NVDA --earnings

# Specific indicators only
uv run python scripts/technicals.py TSLA --indicators rsi,macd

Correlation Analysis

Compute price correlation matrix between multiple symbols for diversification analysis.

Instructions

bash
uv run python scripts/correlation.py SYMBOLS [--period PERIOD]

Arguments

  • SYMBOLS - Comma-separated ticker symbols (minimum 2)
  • --period - Historical period: 1mo, 3mo, 6mo, 1y (default: 3mo)

Output

  • symbols - List of symbols analyzed
  • period - Time period used
  • correlation_matrix - Nested dict with correlation values between all pairs

Interpretation

  • Correlation near 1.0 = highly correlated (move together)
  • Correlation near -1.0 = negatively correlated (move opposite)
  • Correlation near 0 = uncorrelated (independent movement)
  • For diversification, prefer low/negative correlations

Examples

bash
# Portfolio correlation
uv run python scripts/correlation.py AAPL,MSFT,GOOGL,AMZN

# Sector comparison
uv run python scripts/correlation.py XLF,XLK,XLE,XLV --period 6mo

# Check hedge effectiveness
uv run python scripts/correlation.py SPY,GLD,TLT

Dependencies

  • numpy
  • pandas
  • pandas-ta
  • yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.

© staskh, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts) in .claude/skills/technical-analysis of staskh/trading_skills.

  • SKILL.md
  • scripts/correlation.py
  • scripts/technicals.py

Open the folder on GitHubat commit b71a74f

Compare with similar skills

Technical Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Technical Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Technical Analysis this skillstaskh/trading_skills374—~990Automated safety check: PassMIT
Technical Analysttradermonty/claude-trading-skills3k5 repos~4.6kAutomated safety check: PassMIT
Creating Financial ModelsChen-zexi/open-ptc-agent7304 repos~1.3kAutomated safety check: PassMIT
Theme Detectortradermonty/claude-trading-skills3k2 repos~4.9kAutomated safety check: PassMIT
Stock APIzhangxiangliang/stock-api2k—~507Automated safety check: PassMIT
Itr Walakaranb192/itr-wala871—~3.6kAutomated safety check: PassMIT

Similar skills

  • Technical Analyst

    tradermonty/claude-trading-skills

    This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.

    3k GitHub starsUsed in 5 repos~4.6k tokens
    Business, Finance & HRAuto-check passed

  • Creating Financial Models

    Chen-zexi/open-ptc-agent

    This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions

    730 GitHub starsUsed in 4 repos~1.3k tokens
    Business, Finance & HRAuto-check passed

  • Theme Detector

    tradermonty/claude-trading-skills

    Detect and analyze trending market themes across sectors. An agent skill from tradermonty/claude-trading-skills.

    3k GitHub starsUsed in 2 repos~4.9k tokens
    Business, Finance & HRAuto-check passed

  • Stock API

    zhangxiangliang/stock-api

    Fetch real-time stock quotes, K-line (candlestick) history, and search symbols for China A-shares, Hong Kong, and US markets.

    2k GitHub stars~507 tokensUpdated today
    Business, Finance & HRAuto-check passed

  • Itr Wala

    karanb192/itr-wala

    File Indian income tax returns (ITR) for FY 2025-26 / AY 2026-27.

    871 GitHub stars~3.6k tokensUpdated 3 days ago
    Business, Finance & HRAuto-check passed

  • Tushare Data

    zillionare/zillionare

    面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求，转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。

    318 GitHub starsUsed in 2 repos~2.3k tokens
    Business, Finance & HRAuto-check passed

More from staskh/trading_skills

All 28 skills in this repo

  • Fundamentals

    staskh/trading_skills

    Get fundamental financial data including financials, earnings, and key metrics.

    374 GitHub stars~836 tokensUpdated 8 days ago
    Auto-check passed

  • Greeks

    staskh/trading_skills

    Calculate option Greeks (delta, gamma, theta, vega) and implied volatility for specific options.

    374 GitHub stars~539 tokensUpdated 8 days ago
    Auto-check passed

  • Ib Account

    staskh/trading_skills

    Get account summary from Interactive Brokers including cash balance, buying power, and account value.

    374 GitHub stars~535 tokensUpdated 8 days ago
    Auto-check: notes

  • Ib Find Short Roll

    staskh/trading_skills

    Find roll options for existing short positions OR find best covered call/put to open against long stock.

    374 GitHub stars~1.2k tokensUpdated 8 days ago
    Auto-check: notes

  • Ib Option Chain

    staskh/trading_skills

    Get option chain data from Interactive Brokers for equities, ETFs, and futures (FOP), including calls and puts with strikes, bids, asks, volume, implied volatility, and model Greeks.

    374 GitHub stars~873 tokensUpdated 8 days ago
    Auto-check: notes

  • Ib Portfolio

    staskh/trading_skills

    Get portfolio positions from Interactive Brokers. An agent skill from staskh/trading_skills.

    374 GitHub stars~471 tokensUpdated 8 days ago
    Auto-check: notes

Categories

Questions about Technical Analysis

What does Technical Analysis do?

Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock. Technical Analysis is an agent skill from staskh/trading_skills. Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock.

When should I use Technical Analysis?

Technical Analysis fits situations like: user asks about technical analysis; moving averages; overbought/oversold.

How do I install Technical Analysis in Claude Code?

Run `npx skills add staskh/trading_skills --skill technical-analysis -a claude-code`. Or copy the skill folder (.claude/skills/technical-analysis in staskh/trading_skills) into .claude/skills/technical-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Technical Analysis in Codex?

Run `npx skills add staskh/trading_skills --skill technical-analysis -a codex`. Or copy the skill folder (.claude/skills/technical-analysis in staskh/trading_skills) into .agents/skills/technical-analysis in your project. Codex loads it when a task matches its description.

Can I use Technical Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add staskh/trading_skills --skill technical-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/technical-analysis, .gemini/skills/technical-analysis, .github/skills/technical-analysis and .opencode/skills/technical-analysis in your project.

What does Technical Analysis need to run?

Going by SKILL.md and its folder, Technical Analysis needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Technical Analysis access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Technical Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Technical Analysis use?

Technical Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Technical Analysis use?

About 990 tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Technical Analysis?

Skills that share tags, products or a category with Technical Analysis: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 730 stars), Theme Detector (tradermonty/claude-trading-skills, 3k stars) and Stock API (zhangxiangliang/stock-api, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Technical Analysis?

staskh (a GitHub user) maintains it in staskh/trading_skills, which has 374 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on September 28, 2026.

Source: staskh/trading_skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.