risk-management · 0xhubed — Claude Code skill: what it does, how to install
Provides risk management rules learned from 8500 competition trade outcomes. It guides agents when calculating position sizes and setting stop-losses.
npx skills add 0xhubed/agent-trading-arena --skill risk-management -a claude-codeWhat risk-management does
This skill supplies 54 active risk management rules generated by the Observer Agent from 8500 competition trades. Its baseline principles cap single-trade exposure at 2% of equity, require stop-losses on every position, mandate smaller sizes in volatile conditions, and forbid adding to losing trades.
Each pattern includes historical success rates, sample sizes, and confidence ratings. When all five tracked assets gain over 5% within 24 hours, the skill instructs agents to stop short entries completely. Sizing at 2% equity risk with a 2:1 reward ratio succeeds only when aligned with prevailing market direction — without trend validation, the exact same setup fails.
What it helps with
- Size trading positions to cap risk at 2% equity
- Halt short entries when all five tracked assets rise over 5%
- Cap trade frequency to 10 orders per day during bull trends
- Set stop-loss levels for every new position
Example prompts for the agent
- Calculate position size with a 2% equity risk limit and assign a stop-loss
- Check 24-hour performance across the 5 tracked assets before opening a short
- Apply risk-management rules to limit trade frequency today
How to install risk-management
1Skills CLI (Vercel)
npx skills add 0xhubed/agent-trading-arena --skill risk-management -a claude-code2Manually: put the files in place
~/.claude/skills/risk-management/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/risk-management/
1Skills CLI (Vercel)
npx skills add 0xhubed/agent-trading-arena --skill risk-management -a codex2Manually: put the files in place
.agents/skills/risk-management/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add 0xhubed/agent-trading-arena --skill risk-management -a cursor2Manually: put the files in place
.cursor/skills/risk-management/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install 0xhubed/agent-trading-arena risk-management2Manually: put the files in place
.github/skills/risk-management/SKILL.md1Skills CLI (Vercel)
npx skills add 0xhubed/agent-trading-arena --skill risk-management -a gemini-cli2Platform CLI
gemini skills install https://github.com/0xhubed/agent-trading-arena --path .claude/skills/risk-managementManually: put the files in place
.devin/skills/risk-management/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add 0xhubed/agent-trading-arena --skill risk-management -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about risk-management
How do I install risk-management in Claude Code?
Run npx skills add 0xhubed/agent-trading-arena --skill risk-management -a claude-code or save the definition to ~/.claude/skills/risk-management/SKILL.md.
What does the risk-management skill do?
It provides trading agents with empirical drawdown and position-sizing rules derived from analyzing 8500 competition trades.
How are the rules in risk-management updated?
The patterns and confidence scores are automatically generated and refreshed by the Observer Agent from live trading arena outcomes.
Source text
SKILL.md · MIT
---
name: risk-management
description: Risk management rules learned from competition outcomes. Use when sizing positions or setting stop-losses.
---
# Risk Management
> Last updated: 2026-03-09 20:08 UTC
> Active patterns: 54
> Total samples: 8500
> Confidence threshold: 60%
## Core Principles
These rules are derived from analyzing profitable vs losing trades:
| Rule | Success Rate | Samples | Confidence | Seen |
|------|-------------|---------|------------|------|
| Trade frequency inversely correlates wit... | 95% | 473 | 50% | 1x |
| When ALL 5 tracked assets are positive o... | 95% | 58 | 45% | 1x |
| Position sizing at 2% equity risk with 2... | 92% | 183 | 90% | 1x |
| Position sizing at 2% equity risk with 2... | 92% | 200 | 95% | 1x |
| Cap trade frequency at 10 trades/24h max... | 90% | 84 | 45% | 1x |
| Closing LONG positions quickly to pivot ... | 88% | 50 | 95% | 1x |
| Trade frequency must be inversely propor... | 88% | 109 | 45% | 1x |
| Multi-timeframe bearish alignment (15m, ... | 88% | 383 | 99% | 2x |
| In uniformly bearish markets, 'low-sever... | 85% | 49 | 85% | 1x |
| Validation checks passing ('validation p... | 85% | 200 | 95% | 1x |
| High trade frequency (189-200 trades/24h... | 85% | 389 | 95% | 1x |
| When ALL 5 tracked assets are positive o... | 85% | 113 | 95% | 1x |
| Position sizing at 2% equity risk with 2... | 80% | 49 | 85% | 1x |
| Self-reflective position management (jou... | 80% | 48 | 80% | 1x |
| Forum/social sentiment filtering provide... | 80% | 24 | 95% | 1x |
| Closing SHORT positions 'to lock in gain... | 78% | 48 | 85% | 1x |
| Low leverage (2x) on SHORT positions wit... | 75% | 48 | 85% | 1x |
| Position sizing at 2% equity risk with 2... | 75% | 172 | 90% | 1x |
| Low trade frequency (<40 trades/24h) pre... | 75% | 48 | 95% | 1x |
| In uniformly bearish markets, SHORT-bias... | 75% | 3 | 41% | 1x |
| Avoid momentum-following strategies in m... | 75% | 33 | 95% | 1x |
| Self-reflective position management (rec... | 75% | 27 | 95% | 1x |
| Contrarian strategies underperform in mi... | 70% | 16 | 82% | 1x |
| Cap trade frequency at 15 trades/24h max... | 70% | 113 | 95% | 1x |
| Cap trade frequency at 16 trades/24h max... | 67% | 86 | 65% | 1x |
| In mixed/low-volatility markets (daily m... | 67% | 146 | 95% | 1x |
| Self-reflective position management (jou... | 65% | 65 | 45% | 1x |
| Multi-timeframe bearish alignment (15m, ... | 50% | 337 | 90% | 1x |
| High trade frequency (165-172 trades/24h... | 50% | 337 | 90% | 1x |
| High trade frequency (183 trades/24h) ca... | 50% | 366 | 90% | 1x |
| In uniformly bearish markets with mild d... | 50% | 6 | 57% | 1x |
| Validation checks passing ('all checks p... | 41% | 998 | 94% | 2x |
| Closing positions due to 'conflicting ti... | 35% | 20 | 80% | 1x |
| Trade frequency inversely correlates wit... | 33% | 86 | 65% | 1x |
| Cutting small losses quickly (-$0.14 to ... | 30% | 131 | 90% | 1x |
| Cutting small losses quickly (-$38 on SO... | 30% | 147 | 95% | 1x |
| Contrarian LONG entries in bullish marke... | 30% | 6 | 62% | 1x |
| Closing positions 'to reduce concentrati... | 30% | 708 | 99% | 3x |
| Closing positions 'to reduce concentrati... | 25% | 165 | 90% | 1x |
| Validation checks passing ('all checks p... | 25% | 501 | 95% | 1x |
| High concentration warnings (127% of equ... | 25% | 166 | 95% | 1x |
| Multi-timeframe alignment (15m, 1h, 4h) ... | 15% | 298 | 50% | 1x |
| Low trade frequency (<20 trades/24h) in ... | 15% | 25 | 95% | 1x |
| Position sizing at 2% equity risk with 2... | 15% | 166 | 95% | 1x |
| 2% equity risk with 2:1 reward ratio con... | 15% | 58 | 45% | 1x |
| 2% equity risk with 2:1 reward ratio FAI... | 10% | 31 | 95% | 1x |
| Cutting small losses quickly (-$0.01 to ... | 5% | 152 | 90% | 1x |
| Position sizing at 2% equity risk with 2... | 0% | 334 | 50% | 1x |
| High leverage (4x-5x) with 'optimal' ris... | 0% | 132 | 50% | 1x |
| Self-reflective position management (jou... | 0% | 62 | 65% | 1x |
| Low-frequency LONG entries in a bearish ... | 0% | 4 | 43% | 1x |
| Contrarian LONG entries in uniformly bea... | 0% | 9 | 53% | 1x |
| Skill-aware validation frameworks (2% eq... | 0% | 27 | 90% | 1x |
| Contrarian LONG entries in bearish marke... | 0% | 11 | 67% | 1x |
## Top Risk Rules
### Trade frequency inversely correlates with performance in bullish markets: 8 trades = $0.00, 30-34 trades = -$46 to -$51, 120-166 trades = -$41 to -$135
- Success rate: 95%
- Based on 473 observations
- Confidence: 50% (seen 1 times)
- First identified: 2026-01-28
### When ALL 5 tracked assets are positive over 24h with gains exceeding +5%, immediately halt ALL SHORT entries regardless of any lower-timeframe signals, validation checks, or risk calculators.
- Success rate: 95%
- Based on 58 observations
- Confidence: 45% (seen 1 times)
- First identified: 2026-03-04
### Position sizing at 2% equity risk with 2:1 reward ratio SUCCEEDS when agent maintains SHORT bias in bearish markets and uses validation to confirm market direction alignment.
- Success rate: 92%
- Based on 183 observations
- Confidence: 90% (seen 1 times)
- First identified: 2026-01-31
### Position sizing at 2% equity risk with 2:1 reward ratio SUCCEEDS when market direction aligns with position bias and agent maintains high trade frequency (150-200/24h).
- Success rate: 92%
- Based on 200 observations
- Confidence: 95% (seen 1 times)
- First identified: 2026-02-01
### Cap trade frequency at 10 trades/24h maximum in strongly bullish markets when agent directional bias is uncertain. qwen35_skill_aware's 7 trades (+$250.52) vs gptoss_agentic's 28 trades (-$435.19).
- Success rate: 90%
- Based on 84 observations
- Confidence: 45% (seen 1 times)
- First identified: 2026-03-04
## General Guidelines
- Never risk more than 2% of equity on a single trade
- Use stop-losses on every position
- Reduce position size in high volatility regimes
- Don't add to losing positions
---
## Confidence Guide
| Confidence | Interpretation |
|------------|----------------|
| 90%+ | High confidence - strong historical support |
| 70-90% | Moderate confidence - use with other signals |
| 60-70% | Low confidence - consider as one input |
| <60% | Experimental - needs more data |
*This skill is automatically generated and updated by the Observer Agent.*
© 0xhubed · MIT · 0xhubed/agent-trading-arena
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