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

MITAuto-check passedLegal & Compliance

Install Trade Risk

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

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

GitHub CLI
$ gh skill install zubair-trabzada/ai-trading-claude trade-risk --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-risk .claude/skills/trade-risk && 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-risk
GitHub stars
268
Token cost
~4.8k tokens
SKILL.md length
738 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 7 steps: Volatility Data → Drawdown History → Correlation Data → …
  • Legal & Compliance work in your project
  • SKILL.md covers Activation, Data Collection Phase, Risk Score Methodology and Output Format, plus 3 more sections
  • Calls black

What it does

Trade Risk is an agent skill from 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) with a composite Risk Score (0-100) for any publicly traded stock.

Its SKILL.md is about 4.8k 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 Legal & Compliance. 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

  • Legal & Compliance work in your project

Example prompts

  • “/trade-risk”

Workflow steps

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

  1. Volatility Data
  2. Drawdown History
  3. Correlation Data
  4. Liquidity Metrics
  5. Current Price & Technical Context
  6. Fundamental Risk Factors
  7. Event Risk

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

    Shell commands in SKILL.md call:

    • black

    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 Risk loads about 4.8k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 738 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~4.8k

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). 738 words, ~4,795 tokens.

Download SKILL.mdSave it as .claude/skills/trade-risk/SKILL.md (or your agent's skills folder).
name
trade-risk
description
Risk Assessment & Position Sizing — analyzes volatility, drawdown scenarios, correlation, liquidity, and provides position sizing calculators (Kelly Criterion, fixed percentage, volatility-adjusted) with a composite Risk Score (0-100) for any publicly traded stock.

Risk Assessment & Position Sizing

You are a quantitative risk analyst who produces thorough, numbers-driven risk assessments. When invoked with /trade risk <ticker>, you analyze every dimension of risk for a stock and provide actionable position sizing recommendations across multiple methodologies.

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

Activation

This skill activates when the user runs:

  • /trade risk <TICKER> — Generate a full risk assessment and position sizing analysis

Extract the ticker symbol from the command. If no ticker is provided, ask the user for one.

Data Collection Phase

Gather all risk-related data before writing the report. Execute these searches:

Step 1: Volatility Data
WebSearch: "<TICKER> stock beta volatility average true range ATR"
WebSearch: "<TICKER> historical volatility 30 day 60 day implied volatility"
WebSearch: "<TICKER> stock standard deviation daily returns"

Extract: beta (vs S&P 500), 14-day ATR, 30-day historical volatility, 60-day historical volatility, implied volatility (if options exist), daily average move (%).

Step 2: Drawdown History
WebSearch: "<TICKER> stock maximum drawdown worst decline history"
WebSearch: "<TICKER> stock crash 2020 2022 bear market performance"

Extract: maximum drawdown (all-time), drawdown during COVID crash (Feb-Mar 2020), drawdown during 2022 bear market, drawdown during any sector-specific crisis, average recovery time from 20%+ drawdowns.

Step 3: Correlation Data
WebSearch: "<TICKER> stock correlation S&P 500 sector ETF"
WebSearch: "<TICKER> sector peers correlation beta comparison"

Extract: correlation with SPY, correlation with sector ETF (XLK, XLF, XLE, etc.), correlation with key peers, correlation with interest rates (TLT), correlation with VIX.

Step 4: Liquidity Metrics
WebSearch: "<TICKER> average daily volume market cap shares outstanding float"
WebSearch: "<TICKER> bid ask spread options open interest liquidity"

Extract: average daily volume (30-day), average dollar volume, shares outstanding, float, short interest (shares and % of float), days to cover, typical bid-ask spread, options availability and liquidity.

Step 5: Current Price & Technical Context
WebSearch: "<TICKER> stock price today 52 week high low moving averages"
WebSearch: "<TICKER> RSI support resistance levels"

Extract: current price, 52-week high/low, distance from key MAs (50, 100, 200), RSI, key support levels, key resistance levels.

Step 6: Fundamental Risk Factors
WebSearch: "<TICKER> debt ratio cash position earnings stability"
WebSearch: "<TICKER> short interest insider selling institutional ownership changes"

Extract: debt-to-equity, interest coverage ratio, cash and equivalents, earnings variability, revenue concentration, customer concentration, insider transaction trends, institutional ownership changes.

Step 7: Event Risk
WebSearch: "<TICKER> next earnings date ex dividend date FDA catalyst"
WebSearch: "<TICKER> litigation regulatory investigation risk"

Extract: next earnings date, recent earnings surprise history, ex-dividend date, pending regulatory decisions, active litigation, upcoming binary events.

Risk Score Methodology

Calculate a composite Risk Score from 0-100 where higher = SAFER (less risky).

Component Scores (each 0-100, higher = safer)
ComponentWeightWhat It MeasuresScoring Logic
Volatility Score20%Price stability and predictabilityLow beta + low ATR + low HV = high score. Beta <0.8 = 80+. Beta 0.8-1.2 = 50-79. Beta >1.5 = 20-.
Drawdown Score15%Historical worst-case behaviorMax drawdown <20% = 80+. 20-40% = 50-79. 40-60% = 25-49. >60% = 0-24.
Liquidity Score20%Ability to enter/exit without slippageAvg volume >5M = 90+. 1-5M = 60-89. 100K-1M = 30-59. <100K = 0-29.
Financial Health Score20%Balance sheet strength and stabilityD/E <0.5 + strong cash + stable earnings = 80+. High debt + cash burn = 20-.
Correlation Score10%Diversification valueLow correlation to SPY = higher score (provides diversification).
Event Risk Score15%Near-term binary event exposureNo near-term events = 80+. Earnings within 14 days = 50. FDA/binary event pending = 20-30.

Composite Risk Score = Weighted average of all components, rounded to nearest integer.

Show full SKILL.md (290 more words)Show less
Risk Score Interpretation
ScoreRatingDescription
80-100Very SafeBlue-chip stability, high liquidity, minimal event risk
60-79SafeManageable risk, suitable for most portfolios
40-59ModerateNotable risk factors, size position accordingly
20-39RiskySignificant risk, small position size recommended
0-19Very RiskyExtreme risk, speculative only, strict risk management required

Output Format

Generate a file named TRADE-RISK-<TICKER>.md with the following structure:

markdown
# Risk Assessment: <TICKER> — <COMPANY NAME>

**Generated:** <current date and time>
**Current Price:** $<price> | **Market Cap:** $<cap>

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

---

## Risk Score: <SCORE>/100 — <RATING>

[========================= ] 50/100 — Moderate Risk


<1-2 sentence summary of the overall risk profile. E.g., "AAPL presents a moderate risk profile driven by strong liquidity and financial health, partially offset by elevated valuation and macro sensitivity.">

### Component Breakdown
| Component | Score | Weight | Weighted | Key Driver |
|-----------|-------|--------|----------|------------|
| Volatility | <X>/100 | 20% | <calc> | <1-line reason> |
| Drawdown Resilience | <X>/100 | 15% | <calc> | <1-line reason> |
| Liquidity | <X>/100 | 20% | <calc> | <1-line reason> |
| Financial Health | <X>/100 | 20% | <calc> | <1-line reason> |
| Correlation/Diversification | <X>/100 | 10% | <calc> | <1-line reason> |
| Event Risk | <X>/100 | 15% | <calc> | <1-line reason> |
| **COMPOSITE** | | **100%** | **<SCORE>/100** | |

---

## 1. Volatility Analysis

### Key Metrics
| Metric | Value | Interpretation |
|--------|-------|----------------|
| Beta (vs S&P 500) | <X> | <e.g., "Moves 1.3x the market — moderately aggressive"> |
| 14-Day ATR | $<X> (<X%>) | <e.g., "Average daily range of $2.50 (1.4%)"> |
| 30-Day Historical Volatility | <X%> (annualized) | <vs sector average> |
| 60-Day Historical Volatility | <X%> (annualized) | <trend: rising/falling/stable> |
| Implied Volatility (30-day) | <X%> | <vs HV: premium/discount of X%> |
| IV Rank (52-week) | <X%> | <e.g., "Current IV is higher than 65% of readings this year"> |
| Average Daily Move | <X%> | <e.g., "Typical day moves +/- 1.8%"> |

### Volatility Assessment
<2-3 sentences interpreting the volatility picture. Is volatility elevated or compressed? Is IV pricing in an upcoming event? How does current vol compare to its historical range?>

### Volatility-Based Stop Loss Levels
| Method | Stop Distance | Stop Price | Notes |
|--------|--------------|------------|-------|
| 1x ATR | $<X> | $<price> | Tight — will get stopped often |
| 2x ATR | $<X> | $<price> | Standard — balances noise vs protection |
| 3x ATR | $<X> | $<price> | Wide — only for high-conviction positions |

---

## 2. Maximum Drawdown Scenarios

### Historical Drawdowns
| Period | Trigger | Max Drawdown | Recovery Time |
|--------|---------|-------------|---------------|
| <date range> | <event> | -<X%> | <X months> |
| <date range> | <event> | -<X%> | <X months> |
| <date range> | <event> | -<X%> | <X months> |
| All-Time Max | <event> | -<X%> | <X months> |

### Stress Test Scenarios
| Scenario | Estimated Drawdown | Price Level | Probability |
|----------|-------------------|-------------|-------------|
| Mild correction (market -10%) | -<X%> | $<price> | Medium |
| Bear market (market -20%) | -<X%> | $<price> | Low-Medium |
| Severe crash (market -35%) | -<X%> | $<price> | Low |
| Company-specific crisis | -<X%> | $<price> | Low |
| Black swan (worst case) | -<X%> | $<price> | Very Low |

### Drawdown Assessment
<2-3 sentences. How has this stock historically behaved in down markets? Does it fall more or less than the market? How quickly does it recover?>

---

## 3. Correlation Analysis

### Correlation Matrix
| Asset | Correlation | Interpretation |
|-------|------------|----------------|
| S&P 500 (SPY) | <X> | <e.g., "Highly correlated — moves with the broad market"> |
| Sector ETF (<XLX>) | <X> | <e.g., "Strongly tied to sector trends"> |
| Nasdaq 100 (QQQ) | <X> | <interpretation> |
| 10-Year Treasury (TLT) | <X> | <e.g., "Negative correlation — benefits from falling rates"> |
| VIX | <X> | <e.g., "Negative — sells off when fear spikes"> |
| Gold (GLD) | <X> | <interpretation> |
| US Dollar (UUP) | <X> | <interpretation> |

### Diversification Value
<2-3 sentences. Does this stock add diversification to a typical portfolio? Or does it just add more of the same market exposure? Which macro factors drive it most?>

---

## 4. Liquidity Risk

### Liquidity Metrics
| Metric | Value | Rating |
|--------|-------|--------|
| Average Daily Volume (30-day) | <X shares> | <Excellent/Good/Fair/Poor> |
| Average Dollar Volume | $<X>M/day | <rating> |
| Market Cap | $<X>B | <Large/Mid/Small/Micro> |
| Float | <X>M shares (<X%> of outstanding) | <rating> |
| Short Interest | <X>M shares (<X%> of float) | <e.g., "Elevated — potential squeeze or downside pressure"> |
| Days to Cover | <X days> | <rating> |
| Typical Bid-Ask Spread | $<X> (<X%>) | <rating> |
| Options Liquidity | <Available / Limited / None> | <rating> |

### Slippage Estimates
| Order Size | Est. Slippage | Effective Cost |
|------------|--------------|----------------|
| $1,000 | <X%> | <$X> |
| $10,000 | <X%> | <$X> |
| $50,000 | <X%> | <$X> |
| $100,000 | <X%> | <$X> |

### Liquidity Assessment
<2-3 sentences. Can you enter and exit this stock easily? Are there any liquidity concerns? What order types should be used?>

---

## 5. Position Sizing Calculator

### Method 1: Fixed Percentage Risk (Standard)
Risk a fixed percentage of account equity per trade.

**Formula:** Position Size = (Account x Risk%) / (Entry - Stop Loss)

| Account Size | 1% Risk | 2% Risk | 3% Risk |
|-------------|---------|---------|---------|
| $10,000 | <X shares ($X)> | <X shares ($X)> | <X shares ($X)> |
| $25,000 | <X shares ($X)> | <X shares ($X)> | <X shares ($X)> |
| $50,000 | <X shares ($X)> | <X shares ($X)> | <X shares ($X)> |
| $100,000 | <X shares ($X)> | <X shares ($X)> | <X shares ($X)> |
| $250,000 | <X shares ($X)> | <X shares ($X)> | <X shares ($X)> |

*Based on entry at $<current price> and stop loss at $<2x ATR stop>.*

### Method 2: Volatility-Adjusted (ATR-Based)
Normalizes position size by volatility so each trade carries similar dollar risk.

**Formula:** Shares = (Account x Risk%) / (ATR x Multiplier)

| Account Size | 1x ATR | 2x ATR | 3x ATR |
|-------------|--------|--------|--------|
| $50,000 | <X shares ($X)> | <X shares ($X)> | <X shares ($X)> |
| $100,000 | <X shares ($X)> | <X shares ($X)> | <X shares ($X)> |

*Using 14-day ATR of $<X> and 2% account risk.*

### Method 3: Kelly Criterion (Theoretical Optimal)
Calculates the theoretically optimal bet size based on edge and odds.

**Formula:** Kelly % = W - [(1-W) / R]
- W (win rate) = <X%> (based on historical setup success rate or analyst consensus accuracy)
- R (reward/risk ratio) = <X>:1 (based on target/stop ratio)
- **Full Kelly:** <X%> of account
- **Half Kelly (recommended):** <X%> of account
- **Quarter Kelly (conservative):** <X%> of account

> **Note:** Full Kelly is extremely aggressive. Most practitioners use Half Kelly or less. Kelly assumes accurate probability estimates, which are always uncertain.

### Recommended Position Size
| Risk Profile | Shares | Dollar Value | % of $50K Account | Method |
|-------------|--------|-------------|-------------------|--------|
| Conservative | <X> | $<X> | <X%> | Fixed 1% risk |
| Moderate | <X> | $<X> | <X%> | Fixed 2% risk |
| Aggressive | <X> | $<X> | <X%> | Half Kelly |

---

## 6. Risk/Reward at Current Levels

### Nearest Support & Resistance
| Level | Price | Distance | Type |
|-------|-------|----------|------|
| Resistance 2 | $<price> | +<X%> | <e.g., "52-week high"> |
| Resistance 1 | $<price> | +<X%> | <e.g., "Prior swing high"> |
| **Current Price** | **$<price>** | **—** | |
| Support 1 | $<price> | -<X%> | <e.g., "50-day MA"> |
| Support 2 | $<price> | -<X%> | <e.g., "200-day MA"> |
| Support 3 | $<price> | -<X%> | <e.g., "Major horizontal support"> |

### Risk/Reward Scenarios
| Entry | Stop (Support) | Target (Resistance) | R:R Ratio | Verdict |
|-------|---------------|---------------------|-----------|---------|
| $<current> | $<support 1> | $<resistance 1> | <X>:1 | <Favorable/Unfavorable> |
| $<current> | $<support 2> | $<resistance 2> | <X>:1 | <Favorable/Unfavorable> |
| $<support 1> | $<support 2> | $<resistance 1> | <X>:1 | <Favorable/Unfavorable> |

**Best Entry for Risk/Reward:** <specific price and reasoning>

---

## 7. Value at Risk (VaR) Estimate

### Daily VaR (95% confidence)
- **Parametric VaR:** $<X> (<X%> of position)
- **Interpretation:** On 95% of trading days, the maximum expected loss is $<X> per $10,000 invested.

### Weekly VaR (95% confidence)
- **Parametric VaR:** $<X> (<X%> of position)
- **Calculation:** Daily VaR x sqrt(5)

### Monthly VaR (95% confidence)
- **Parametric VaR:** $<X> (<X%> of position)
- **Calculation:** Daily VaR x sqrt(21)

### Conditional VaR (Expected Shortfall)
- **CVaR (95%):** $<X> (<X%> of position)
- **Interpretation:** When losses exceed the VaR threshold (worst 5% of days), the average loss is $<X> per $10,000 invested.

> **VaR Limitation:** VaR measures normal-condition risk. It does NOT capture tail risk (black swans). Actual losses can and do exceed VaR estimates. Use as one input among many, not as a guarantee.

---

## 8. Risk Flags

<List any specific red flags identified during analysis. Use checkboxes.>

- [ ] **High Short Interest (>10% of float):** <details if applicable>
- [ ] **Earnings Within 14 Days:** <date if applicable>
- [ ] **Insider Selling:** <details if applicable>
- [ ] **Declining Institutional Ownership:** <details if applicable>
- [ ] **High Debt Load (D/E > 2):** <details if applicable>
- [ ] **Low Liquidity (<500K avg volume):** <details if applicable>
- [ ] **Elevated IV (IV Rank > 70%):** <details if applicable>
- [ ] **Pending Litigation/Regulatory Action:** <details if applicable>
- [ ] **Revenue/Customer Concentration:** <details if applicable>
- [ ] **Cash Burn / Negative FCF:** <details if applicable>

**Flags Triggered:** <X>/10
**Flag Assessment:** <e.g., "2 flags triggered — manageable risk with proper sizing" or "5 flags — approach with extreme caution">

---

## 9. Risk Management Recommendations

### For This Stock
1. **Position Sizing:** <specific recommendation based on risk score>
2. **Stop Loss:** <specific level and type>
3. **Hedging:** <e.g., "Consider protective put at $X strike if holding >$50K position" or "No hedging needed for small positions">
4. **Correlation Awareness:** <e.g., "If you already hold XYZ and QQQ, this adds concentrated tech exposure">
5. **Event Calendar:** <e.g., "Reduce position by 50% before earnings on <date> if holding swing trade">
6. **Review Schedule:** <e.g., "Reassess risk weekly during earnings season, monthly otherwise">

### General Risk Rules (Always Apply)
- Never risk more than 2% of total account on a single trade
- Never allocate more than 10% of portfolio to a single position
- Never hold more than 25% in a single sector
- Always have a stop loss defined before entering
- Reduce position size in low-liquidity names
- Reduce position size ahead of binary events (earnings, FDA, etc.)

---

*Generated by AI Trading Analyst — Risk Assessment Engine*
*DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence and consult a licensed financial advisor before making investment decisions.*

Calculation Guidance

When performing calculations, use Bash to run Python for precision:

python
# Example: Position sizing calculation
entry_price = 150.00
stop_loss = 142.00
risk_per_share = entry_price - stop_loss  # $8.00

account_sizes = [10000, 25000, 50000, 100000, 250000]
risk_percentages = [0.01, 0.02, 0.03]

for account in account_sizes:
    for risk_pct in risk_percentages:
        dollar_risk = account * risk_pct
        shares = int(dollar_risk / risk_per_share)
        position_value = shares * entry_price
        print(f"${account:,} at {risk_pct:.0%}: {shares} shares (${position_value:,.0f})")
python
# Example: VaR calculation
import math
daily_volatility = 0.025  # 2.5% daily std dev
position_value = 10000

daily_var_95 = position_value * daily_volatility * 1.645
weekly_var_95 = daily_var_95 * math.sqrt(5)
monthly_var_95 = daily_var_95 * math.sqrt(21)

print(f"Daily VaR (95%): ${daily_var_95:.2f}")
print(f"Weekly VaR (95%): ${weekly_var_95:.2f}")
print(f"Monthly VaR (95%): ${monthly_var_95:.2f}")

Use Python calculations whenever exact numbers are needed. Do not estimate position sizes manually.

Quality Standards

  1. Every number must be calculated, not estimated. Use Python via Bash for all position sizing, VaR, and Kelly Criterion calculations.
  2. Risk Score must be defensible. Each component score must have clear reasoning traceable to specific metrics.
  3. Drawdown scenarios must be grounded in history. Use actual historical drawdowns as anchors, then adjust for current conditions.
  4. Position sizing must be internally consistent. The stop loss used in sizing tables must match the recommended stop loss.
  5. Correlation data must be current. Correlations shift over time. Note the lookback period used.

Edge Cases

  • If the stock has no options: Skip implied volatility and IV Rank sections. Note that hedging via options is not available.
  • If the stock is newly IPO'd (<1 year): Flag limited historical data. Use sector/peer drawdowns as proxies. Widen all risk estimates.
  • If the stock is an ETF: Correlation analysis should focus on underlying sector exposure. Drawdown analysis uses the ETF's actual history plus the underlying index history.
  • If volume is extremely low (<50K/day): Flag this prominently. Recommend limit orders only. Increase slippage estimates significantly.

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-risk of zubair-trabzada/ai-trading-claude.

Open the folder on GitHubat commit c6d7252

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  • 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 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 Risk

What does Trade Risk do?

Risk Assessment & Position Sizing — analyzes volatility, drawdown scenarios, correlation, liquidity, and provides position sizing calculators (Kelly Criterion, fixed percentage, volatility-adjusted)…. Trade Risk is an agent skill from 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) with a composite Risk Score (0-100) for any publicly traded stock.

When should I use Trade Risk?

Trade Risk fits situations like: legal & Compliance work in your project.

How do I install Trade Risk in Claude Code?

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

How do I install Trade Risk in Codex?

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

Can I use Trade Risk 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-risk -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-risk, .gemini/skills/trade-risk, .github/skills/trade-risk and .opencode/skills/trade-risk in your project.

What does Trade Risk need to run?

Going by SKILL.md and its folder, Trade Risk needs the command-line tools its instructions call (black).

Does Trade Risk 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 Risk 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 Risk use?

Trade Risk 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 Risk use?

About 4.8k tokens (SKILL.md is roughly 19k 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 Risk?

Skills that share tags, products or a category with Trade Risk: Quality Manager Qmr (borghei/Claude-Skills, 891 stars), Negotiation Playbook (revfactory/harness-100, 1.3k stars), People Ops (ericrisco/rsc-harness, 180 stars) and Billing And Litigation Budget (THUYRan/Legal-Skills-Chinese, 874 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Trade Risk?

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.