Full Stock Analysis Orchestrator — launches 5 parallel subagents for comprehensive multi-dimensional stock analysis with composite Trade Score

MITAuto-check passedBusiness, Finance & HR

Install Trade Analyze

skills CLI
$ npx skills add zubair-trabzada/ai-trading-claude --skill trade-analyze -a claude-code

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

GitHub CLI
$ gh skill install zubair-trabzada/ai-trading-claude trade-analyze --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/zubair-trabzada/ai-trading-claude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/trade-analyze .claude/skills/trade-analyze && 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
trade-analyze
GitHub stars
268
Token cost
~4.9k tokens
SKILL.md length
792 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Full Stock Analysis Orchestrator — launches 5 parallel subagents for comprehensive multi-dimensional stock analysis with composite Trade Score

  • Works in 3 steps: Discovery (You Do This Directly) → Parallel Agent Deployment → Synthesis & Report Generation
  • Tasks that involve Stock and market analysis
  • SKILL.md covers Execution Flow, Error Handling and Important Rules
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Trade Analyze is an agent skill from zubair-trabzada/ai-trading-claude. Full Stock Analysis Orchestrator — launches 5 parallel subagents for comprehensive multi-dimensional stock analysis with composite Trade Score

Its SKILL.md is about 4.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Stock and market analysis and Subagents. The repository describes itself as: AI trading research engine for Claude Code. Analyze stocks (technical, fundamental, sentiment, risk, thesis), options strategies, sector rotation, portfolio analysis, and PDF… The licence is MIT.

When your agent uses it

  • Tasks that involve Stock and market analysis
  • Tasks that involve Subagents

Example prompts

  • “/trade-analyze”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Discovery (You Do This Directly)
  2. Parallel Agent Deployment
  3. Synthesis & Report Generation

What it can do on your machine

Read from SKILL.md and the folder at commit c6d7252. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

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

  • Network

    No URLs in SKILL.md.

    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

Trade Analyze loads about 4.9k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 792 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~4.9k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from zubair-trabzada/ai-trading-claude at commit c6d7252, republished under its MIT licence (© zubair-trabzada). 792 words, ~4,931 tokens.

Download SKILL.mdSave it as .claude/skills/trade-analyze/SKILL.md (or your agent's skills folder).
name
trade-analyze
description
Full Stock Analysis Orchestrator — launches 5 parallel subagents for comprehensive multi-dimensional stock analysis with composite Trade Score

Full Stock Analysis Orchestrator

You are the flagship analysis engine for the AI Trading Analyst system. When invoked with /trade analyze <TICKER>, you perform the most comprehensive stock analysis available in this toolkit by launching 5 parallel subagents and synthesizing their findings into a unified Trade Score and investment report.

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.


Execution Flow

There are three distinct phases. Execute them in strict order.

PHASE 1: Discovery (You Do This Directly)

Before launching any agents, YOU must gather the foundational data they all need. This prevents 5 agents from redundantly searching for the same basic information.

Step 1 — Current Price & Market Context

Use WebSearch to find:

  • Current stock price for TICKER
  • Today's price change (dollar and percentage)
  • Market cap and cap category (Large/Mid/Small/Micro)
  • Average daily volume
  • 52-week high and 52-week low
  • Sector and industry classification
  • S&P 500 / relevant index performance for context

Search query pattern: "<TICKER> stock price today market cap 2026"

Step 2 — Company Overview

Use WebSearch to find:

  • Company description (what they do, in 2-3 sentences)
  • Key products or revenue segments
  • CEO and notable leadership
  • Number of employees (approximate)
  • Headquarters location
  • When they went public / IPO date if relevant

Search query pattern: "<TICKER> company overview business description"

Step 3 — Recent News & Catalysts

Use WebSearch to find:

  • Last 5-10 major headlines about the company (past 30 days)
  • Any upcoming earnings date
  • Recent earnings results (last quarter EPS beat/miss, revenue beat/miss)
  • Any major announcements (product launches, partnerships, acquisitions, lawsuits)
  • Macro headwinds or tailwinds affecting the sector

Search query pattern: "<TICKER> stock news latest 2026"

Step 4 — Key Financial Metrics Snapshot

Use WebSearch to find:

  • P/E ratio (trailing and forward)
  • Revenue (TTM) and YoY growth rate
  • EPS (TTM) and YoY growth rate
  • Profit margins (gross, operating, net)
  • Debt-to-equity ratio
  • Free cash flow (TTM)
  • Dividend yield (if applicable)
  • Short interest (% of float)

Search query pattern: "<TICKER> financial ratios P/E revenue earnings 2026"

Compile the Discovery Brief. Organize all findings into a structured block of text that you will pass to every subagent. This is the DISCOVERY_BRIEF.


PHASE 2: Parallel Agent Deployment

Launch exactly 5 agents using the Agent tool. All 5 MUST be launched in a single message so they run in parallel. Do NOT wait for one to finish before launching the next.

Each agent receives:

  1. The full DISCOVERY_BRIEF from Phase 1
  2. A specific analysis mandate (detailed below)
  3. Instructions to return a structured score and analysis

CRITICAL: Launch all 5 agents in the SAME response. This is what makes the analysis fast.


Agent 1: Technical Analysis (Weight: 25%)
Agent tool prompt:

You are a Technical Analysis specialist. Analyze <TICKER> using the discovery data below and your own additional research via WebSearch.

DISCOVERY DATA:
<insert DISCOVERY_BRIEF here>

YOUR MANDATE — Deliver a comprehensive technical analysis covering:

1. TREND ANALYSIS
   - Primary trend direction (bullish / bearish / sideways)
   - EMA 20/50/200 alignment and slope
   - Price position relative to key moving averages
   - Higher highs / higher lows pattern (or inverse)

2. SUPPORT & RESISTANCE
   - Identify at least 3 support levels with reasoning
   - Identify at least 3 resistance levels with reasoning
   - Note which levels have highest confluence

3. MOMENTUM INDICATORS
   - RSI (14): current value and trend, overbought/oversold status
   - MACD: signal line position, histogram direction, divergences
   - Stochastic: %K/%D position and crossover status

4. VOLUME ANALYSIS
   - Current volume vs 20-day and 50-day average
   - Accumulation/distribution pattern
   - On-Balance Volume (OBV) trend
   - Any volume divergences from price

5. CHART PATTERNS
   - Active patterns (flags, wedges, head & shoulders, cups, double tops/bottoms)
   - Pattern completion percentage and implied target
   - Breakout/breakdown levels

6. ADDITIONAL TECHNICAL FACTORS
   - Bollinger Band position (upper/middle/lower, squeeze status)
   - Moving average crossovers (golden cross, death cross proximity)
   - Relative strength vs SPY over 1-month, 3-month, 6-month periods
   - Fibonacci retracement levels from recent swing

SCORING — Provide a Technical Score (0-100) broken into:
   - Trend Score (0-20): Are moving averages aligned bullishly?
   - Momentum Score (0-20): Are oscillators confirming the trend?
   - Volume Score (0-20): Is volume supporting the price action?
   - Pattern Quality (0-20): Are there clear, actionable patterns?
   - Relative Strength (0-20): Is this outperforming the market?

Return your analysis in this exact format:
## Technical Analysis: <TICKER>
### Technical Score: [X]/100
[Trend: X/20 | Momentum: X/20 | Volume: X/20 | Pattern: X/20 | Rel Strength: X/20]
### Signal: [Bullish / Neutral / Bearish]
[Then provide the full analysis organized by the 6 sections above]
### Key Levels
- Entry Zone: $X - $X
- Stop Loss: $X (X% below entry)
- Target 1: $X (X% upside)
- Target 2: $X (X% upside)

DISCLAIMER: This is for educational and research purposes only. Not financial advice.

Agent 2: Fundamental Analysis (Weight: 25%)
Agent tool prompt:

You are a Fundamental Analysis specialist. Analyze <TICKER> using the discovery data below and your own additional research via WebSearch.

DISCOVERY DATA:
<insert DISCOVERY_BRIEF here>

YOUR MANDATE — Deliver a comprehensive fundamental analysis covering:

1. VALUATION
   - P/E (trailing & forward) vs sector median and 5-year average
   - P/S ratio vs sector
   - P/B ratio vs sector
   - PEG ratio assessment
   - EV/EBITDA vs sector
   - Verdict: Undervalued / Fair Value / Overvalued

2. GROWTH
   - Revenue growth rate (QoQ, YoY, 3-year CAGR)
   - Earnings growth rate (QoQ, YoY, 3-year CAGR)
   - Forward guidance and analyst estimates
   - Total addressable market (TAM) and penetration

3. PROFITABILITY
   - Gross margin and trend
   - Operating margin and trend
   - Net margin and trend
   - Return on Equity (ROE)
   - Return on Invested Capital (ROIC)

4. FINANCIAL HEALTH
   - Debt-to-equity ratio and trend
   - Current ratio and quick ratio
   - Free cash flow and FCF yield
   - Cash position and burn rate (if applicable)
   - Interest coverage ratio

5. COMPETITIVE MOAT
   - Brand strength assessment
   - Network effects (if applicable)
   - Switching costs for customers
   - Cost advantages vs competitors
   - Intangible assets (patents, licenses, data)
   - Overall moat rating: Wide / Narrow / None

6. MANAGEMENT QUALITY
   - Insider ownership percentage
   - CEO track record and tenure
   - Capital allocation history (buybacks, dividends, M&A quality)
   - Alignment with shareholders

SCORING — Provide a Fundamental Score (0-100) broken into:
   - Valuation (0-20): Is the stock reasonably priced?
   - Growth (0-20): Is the company growing meaningfully?
   - Profitability (0-20): Are margins healthy and improving?
   - Financial Health (0-20): Is the balance sheet strong?
   - Moat Strength (0-20): Is there a durable competitive advantage?

Return your analysis in this exact format:
## Fundamental Analysis: <TICKER>
### Fundamental Score: [X]/100
[Valuation: X/20 | Growth: X/20 | Profitability: X/20 | Health: X/20 | Moat: X/20]
### Signal: [Strong / Adequate / Weak]
[Then provide the full analysis organized by the 6 sections above]

DISCLAIMER: This is for educational and research purposes only. Not financial advice.

Agent 3: Sentiment Analysis (Weight: 20%)
Agent tool prompt:

You are a Sentiment & Momentum Analysis specialist. Analyze <TICKER> using the discovery data below and your own additional research via WebSearch.

DISCOVERY DATA:
<insert DISCOVERY_BRIEF here>

YOUR MANDATE — Deliver a comprehensive sentiment analysis covering:

1. NEWS SENTIMENT — Search for recent headlines about <TICKER>. Score each as positive/negative/neutral. Identify major catalysts.

2. SOCIAL MEDIA BUZZ — Search for <TICKER> mentions on Reddit (WallStreetBets, investing), StockTwits, and X/Twitter. Gauge sentiment direction and intensity.

3. ANALYST RATINGS — Find consensus rating (buy/hold/sell), average price target vs current price, and any recent upgrades or downgrades.

4. INSTITUTIONAL ACTIVITY — Search for recent 13F filings, major fund entries or exits, and institutional ownership percentage.

5. INSIDER TRADING — Search for recent insider buys and sells by executives and directors. Flag any cluster buying or large sales.

6. SHORT INTEREST — Find short interest as % of float, days to cover, and assess short squeeze potential.

SCORING — Provide a Sentiment Score (0-100) broken into 5 sub-dimensions (0-20 each).

Return your analysis in this exact format:
## Sentiment Analysis: <TICKER>
### Sentiment Score: [X]/100
[News: X/20 | Social: X/20 | Analysts: X/20 | Institutional: X/20 | Insider/Short: X/20]
### Signal: [Bullish / Neutral / Bearish]
[Then provide the full analysis organized by the 6 sections above]

DISCLAIMER: This is for educational and research purposes only. Not financial advice.

Agent 4: Risk Assessment (Weight: 15%)
Agent tool prompt:

You are a Risk Assessment specialist. Analyze <TICKER> using the discovery data below and your own additional research via WebSearch.

DISCOVERY DATA:
<insert DISCOVERY_BRIEF here>

YOUR MANDATE — Deliver a comprehensive risk assessment covering:

1. VOLATILITY PROFILE
   - Historical volatility (30-day, 90-day)
   - Beta vs S&P 500
   - Average True Range (ATR) and typical daily range
   - Implied volatility from options (if available)

2. DOWNSIDE SCENARIOS
   - Bear case price target with reasoning
   - Maximum drawdown from current price (worst case)
   - Key risk events on the calendar (earnings, FDA dates, etc.)
   - Sector-specific risks

3. CORRELATION & MACRO RISK
   - Correlation with major indices
   - Interest rate sensitivity
   - Currency exposure
   - Commodity input risks
   - Regulatory and geopolitical risks

4. LIQUIDITY RISK
   - Average daily dollar volume
   - Bid-ask spread assessment
   - Institutional ownership concentration
   - Float analysis (free float vs locked shares)

5. POSITION SIZING RECOMMENDATION
   - Suggested position size as % of portfolio (conservative, moderate, aggressive)
   - Recommended stop-loss level and rationale
   - Risk/reward ratio at current price
   - Kelly Criterion estimate (if sufficient data)

6. RISK FACTORS SUMMARY
   - Top 5 risks ranked by probability and severity
   - Risk matrix (probability vs impact for each)
   - Mitigating factors for each risk

SCORING — Provide a Risk Score (0-100) where HIGHER = LOWER RISK (inverted for composite):
   - Volatility (0-20): 20 = low volatility, 0 = extreme volatility
   - Downside Protection (0-20): 20 = limited downside, 0 = major downside risk
   - Macro Resilience (0-20): 20 = macro-resistant, 0 = highly macro-sensitive
   - Liquidity (0-20): 20 = very liquid, 0 = illiquid
   - Risk/Reward (0-20): 20 = excellent risk/reward, 0 = poor risk/reward

Return your analysis in this exact format:
## Risk Assessment: <TICKER>
### Risk Score: [X]/100 (higher = lower risk)
[Volatility: X/20 | Downside: X/20 | Macro: X/20 | Liquidity: X/20 | R/R: X/20]
### Risk Level: [Low / Moderate / High / Extreme]
[Then provide the full analysis organized by the 6 sections above]

DISCLAIMER: This is for educational and research purposes only. Not financial advice.

Agent 5: Thesis Synthesis (Weight: 15%)
Agent tool prompt:

You are an Investment Thesis specialist. Synthesize an investment thesis for <TICKER> using the discovery data below and your own additional research via WebSearch.

DISCOVERY DATA:
<insert DISCOVERY_BRIEF here>

YOUR MANDATE — Build a complete investment thesis covering:

1. CORE THESIS (2-3 sentences)
   - Why this stock, why now, what is the edge

2. BULL CASE
   - 3-5 specific catalysts that could drive the stock higher
   - Bull case price target with timeline
   - What would need to go right

3. BEAR CASE
   - 3-5 specific risks that could drive the stock lower
   - Bear case price target with timeline
   - What would need to go wrong

4. CATALYST CALENDAR
   - Upcoming events that could move the stock (earnings, product launches, regulatory decisions, conferences)
   - Expected dates and potential impact direction

5. ENTRY/EXIT STRATEGY
   - Recommended entry zone with reasoning
   - Recommended stop-loss with reasoning
   - Target 1 (conservative) and Target 2 (aggressive) with reasoning
   - Position sizing suggestion
   - Recommended timeframe (swing trade / position trade / long-term hold)

6. CONVICTION ASSESSMENT
   - What gives you conviction (or lack thereof)
   - What would change the thesis (invalidation triggers)
   - Comparison to opportunity cost (why this over SPY or alternatives)

SCORING — Provide a Thesis Score (0-100) broken into:
   - Catalyst Clarity (0-20): Are there clear, identifiable catalysts?
   - Timing (0-20): Is the timing right for entry?
   - Asymmetry (0-20): Is the risk/reward skewed favorably?
   - Edge (0-20): Is there an identifiable informational or analytical edge?
   - Conviction (0-20): How confident is the overall thesis?

Return your analysis in this exact format:
## Investment Thesis: <TICKER>
### Thesis Score: [X]/100
[Catalyst: X/20 | Timing: X/20 | Asymmetry: X/20 | Edge: X/20 | Conviction: X/20]
### Thesis: [Strong / Moderate / Weak]
[Then provide the full analysis organized by the 6 sections above]

DISCLAIMER: This is for educational and research purposes only. Not financial advice.

Show full SKILL.md (332 more words)Show less
PHASE 3: Synthesis & Report Generation

After ALL 5 agents have returned their results, you synthesize everything into the final report.

Step 1 — Calculate Composite Trade Score

Composite Trade Score = (Technical Score * 0.25) + (Fundamental Score * 0.25) + (Sentiment Score * 0.20) + (Risk Score * 0.15) + (Thesis Score * 0.15)

Round to nearest integer.

Step 2 — Determine Grade and Signal

Score RangeGradeSignal
85-100A+Strong Buy
70-84ABuy
55-69BHold/Accumulate
40-54CNeutral
25-39DCaution
0-24FAvoid

Step 3 — Generate the Unified Report

Write the file TRADE-ANALYSIS-<TICKER>.md to the current working directory with this exact structure:

markdown
# Trade Analysis: <TICKER> — <COMPANY NAME>
> Generated by AI Trading Analyst | <DATE>

---

## Executive Summary

[2-3 paragraph synthesis of the entire analysis. What is this company, what is the setup, and what is the verdict? Write this as if briefing a portfolio manager who has 60 seconds to decide whether to dig deeper.]

---

## Trade Score Dashboard

| Dimension | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Technical Strength | X/100 | 25% | X.X |
| Fundamental Quality | X/100 | 25% | X.X |
| Sentiment & Momentum | X/100 | 20% | X.X |
| Risk Profile | X/100 | 15% | X.X |
| Thesis Conviction | X/100 | 15% | X.X |
| **Composite Trade Score** | | | **X/100** |

**Grade: [X]** | **Signal: [X]**

### Sub-Score Breakdown

**Technical** [X/100]: Trend X/20 | Momentum X/20 | Volume X/20 | Pattern X/20 | Rel Strength X/20
**Fundamental** [X/100]: Valuation X/20 | Growth X/20 | Profitability X/20 | Health X/20 | Moat X/20
**Sentiment** [X/100]: News X/20 | Social X/20 | Analysts X/20 | Institutional X/20 | Insider/Short X/20
**Risk** [X/100]: Volatility X/20 | Downside X/20 | Macro X/20 | Liquidity X/20 | R/R X/20
**Thesis** [X/100]: Catalyst X/20 | Timing X/20 | Asymmetry X/20 | Edge X/20 | Conviction X/20

---

## Technical Overview
[Condensed technical analysis from Agent 1 — key findings, chart setup, important levels]

## Fundamental Overview
[Condensed fundamental analysis from Agent 2 — valuation verdict, growth profile, moat assessment]

## Sentiment Analysis
[Condensed sentiment analysis from Agent 3 — news tone, analyst consensus, smart money signals]

## Risk Assessment
[Condensed risk assessment from Agent 4 — key risks, volatility profile, position sizing]

## Investment Thesis
[Full thesis from Agent 5 — bull case, bear case, catalysts, entry/exit strategy]

---

## Entry/Exit Strategy

| Parameter | Level | Notes |
|-----------|-------|-------|
| Entry Zone | $X - $X | [reasoning] |
| Stop Loss | $X | [X% risk from entry] |
| Target 1 | $X | [X% reward, conservative] |
| Target 2 | $X | [X% reward, aggressive] |
| Risk/Reward | X:1 | [at midpoint entry to T1] |
| Position Size | X% of portfolio | [based on risk tolerance] |
| Timeframe | [swing / position / long-term] | [reasoning] |

---

## Bull vs Bear

| Bull Case | Bear Case |
|-----------|-----------|
| [factor 1] | [factor 1] |
| [factor 2] | [factor 2] |
| [factor 3] | [factor 3] |
| [factor 4] | [factor 4] |
| [factor 5] | [factor 5] |
| **Bull Target: $X** | **Bear Target: $X** |

---

## Catalyst Calendar

| Date | Event | Expected Impact |
|------|-------|-----------------|
| [date] | [event] | [bullish/bearish/neutral] |

---

> **DISCLAIMER:** This analysis is generated by an AI system for educational and research purposes only. It is NOT financial advice. It does NOT constitute a recommendation to buy, sell, or hold any security. Past performance does not indicate future results. Always conduct your own due diligence and consult a licensed financial advisor before making investment decisions. AI-generated analysis may contain errors or outdated information. Verify all data independently.

Step 4 — Confirm Output

After writing the file, display a summary in the terminal:

  • The Trade Score, Grade, and Signal
  • The file path where the report was saved
  • Remind the user this is for educational purposes only

Error Handling

  • If WebSearch fails for any query in Phase 1, retry with a modified query. If it fails again, note the data gap and proceed.
  • If any agent fails or returns an incomplete analysis, note which dimension is missing, exclude it from the weighted score, and recalculate weights proportionally.
  • If the ticker appears to be invalid (no price data found), inform the user and suggest they check the ticker symbol.
  • If the stock is an ETF, adjust the analysis focus per the Market Context Detection rules in the main orchestrator.

Important Rules

  1. ALWAYS complete Phase 1 yourself before launching agents. Agents depend on the Discovery Brief.
  2. ALWAYS launch all 5 agents in a SINGLE message for parallel execution.
  3. NEVER fabricate data. If you cannot find a metric, say "Data not available" rather than guessing.
  4. ALWAYS include specific numbers, prices, and percentages — not vague qualitative statements.
  5. ALWAYS include the full disclaimer in the output report.
  6. ALWAYS note the date of analysis — market data has a shelf life.
  7. ALWAYS present both bull and bear perspectives — never one-sided.
  8. The final report should be comprehensive but scannable — use tables, bold text, and clear headers.

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

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

Files

Just SKILL.md in skills/trade-analyze of zubair-trabzada/ai-trading-claude.

Open the folder on GitHubat commit c6d7252

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    zubair-trabzada/ai-trading-claude

    Fundamental Analysis Agent — valuation, growth, profitability, balance sheet, competitive moat, and management quality analysis with Fundamental Score (0-100)

    268 GitHub stars~4.5k tokensUpdated 6 mo ago
    Auto-check passed
  • Trade Quick

    zubair-trabzada/ai-trading-claude

    60-Second Stock Snapshot — fast assessment with signal, key factors, and levels without launching subagents

    268 GitHub stars~4.6k tokensUpdated 6 mo ago
    Auto-check passed
  • Trade Risk

    zubair-trabzada/ai-trading-claude

    Risk Assessment & Position Sizing — analyzes volatility, drawdown scenarios, correlation, liquidity, and provides position sizing calculators (Kelly Criterion, fixed percentage, volatility-adjusted)…

    268 GitHub stars~4.8k tokensUpdated 6 mo ago
    Auto-check passed
  • Trade Sector

    zubair-trabzada/ai-trading-claude

    Sector Rotation & Analysis — analyzes sector momentum rankings, money flows, economic cycle positioning, relative strength, top stocks per sector, valuations, and rotation signals to identify where…

    268 GitHub stars~4.3k tokensUpdated 6 mo ago
    Auto-check passed
  • Trade Sentiment

    zubair-trabzada/ai-trading-claude

    Sentiment & Momentum Analysis Agent — news sentiment, social media buzz, analyst ratings, institutional activity, insider trading, and short interest with Sentiment Score (0-100)

    268 GitHub stars~4.8k tokensUpdated 6 mo ago
    Auto-check passed

Questions about Trade Analyze

What does Trade Analyze do?

Full Stock Analysis Orchestrator — launches 5 parallel subagents for comprehensive multi-dimensional stock analysis with composite Trade Score. Trade Analyze is an agent skill from zubair-trabzada/ai-trading-claude.

When should I use Trade Analyze?

Trade Analyze fits situations like: tasks that involve Stock and market analysis; tasks that involve Subagents.

How do I install Trade Analyze in Claude Code?

Run `npx skills add zubair-trabzada/ai-trading-claude --skill trade-analyze -a claude-code`. Or copy the skill folder (skills/trade-analyze in zubair-trabzada/ai-trading-claude) into .claude/skills/trade-analyze in your project. Claude Code loads it when a task matches its description.

How do I install Trade Analyze in Codex?

Run `npx skills add zubair-trabzada/ai-trading-claude --skill trade-analyze -a codex`. Or copy the skill folder (skills/trade-analyze in zubair-trabzada/ai-trading-claude) into .agents/skills/trade-analyze in your project. Codex loads it when a task matches its description.

Can I use Trade Analyze 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 zubair-trabzada/ai-trading-claude --skill trade-analyze -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trade-analyze, .gemini/skills/trade-analyze, .github/skills/trade-analyze and .opencode/skills/trade-analyze in your project.

What does Trade Analyze need to run?

SKILL.md names no scripts, command-line tools or credentials: Trade Analyze is instructions for the agent only.

Does Trade Analyze access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Trade Analyze 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. Review the folder before installing.

What licence does Trade Analyze use?

Trade Analyze 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 Trade Analyze use?

About 4.9k tokens (SKILL.md is roughly 20k 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 Trade Analyze?

Skills that share tags, products or a category with Trade Analyze: Invest (longsizhuo/openInvest, 108 stars), Stock API (zhangxiangliang/stock-api, 2k stars), Tushare Data (zillionare/zillionare, 322 stars) and Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Trade Analyze?

zubair-trabzada (a GitHub user) maintains it in zubair-trabzada/ai-trading-claude, which has 268 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on April 7, 2026.

Source: zubair-trabzada/ai-trading-claude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.