risk-management▌
0xhubed/agent-trading-arena · updated May 16, 2026
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Data-driven position sizing and stop-loss rules extracted from 13,385 historical trades.
- ›Prioritize explicit risk validation before entry: trades with documented risk-per-trade checks and 2:1 reward ratios show 92% success rates and +$1,379 average PnL
- ›Adapt trade frequency to market regime: flat markets tolerate 3–6 trades maximum; choppy markets require 0–10 trades per 24 hours; excessive frequency (150+ trades) correlates with losses exceeding $500
- ›Apply position sizing caps: limi
Risk Management
Last updated: 2026-01-17 20:31 UTC Active patterns: 40 Total samples: 13385 Confidence threshold: 60%
Core Principles
These rules are derived from analyzing profitable vs losing trades:
| Rule | Success Rate | Samples | Confidence | Seen |
|---|---|---|---|---|
| Trade count inversely correlates with pe... | 95% | 861 | 55% | 1x |
| Trade frequency should adapt to market r... | 95% | 950 | 95% | 1x |
| Validate risk per trade explicitly befor... | 92% | 157 | 65% | 1x |
| Validate risk per trade explicitly befor... | 92% | 164 | 70% | 1x |
| Trade frequency should adapt to market r... | 92% | 895 | 95% | 1x |
| Trade frequency should adapt to market r... | 92% | 855 | 95% | 1x |
| Validate risk per trade explicitly befor... | 92% | 328 | 79% | 2x |
| Optimal trade frequency in trending bull... | 90% | 543 | 75% | 1x |
| Optimal trade frequency in trending bull... | 88% | 1088 | 79% | 2x |
| Close losing positions proactively with ... | 88% | 184 | 75% | 1x |
| Close short positions immediately when m... | 88% | 675 | 95% | 1x |
| Close losing positions proactively with ... | 88% | 368 | 79% | 2x |
| High confidence (>0.8) should require co... | 85% | 20 | 50% | 1x |
| Close losing positions proactively with ... | 85% | 182 | 65% | 1x |
| Position sizing at 25% equity limit per ... | 85% | 321 | 70% | 1x |
| Diversify across multiple assets (BTC, E... | 85% | 494 | 79% | 2x |
| Close losing positions proactively with ... | 85% | 100 | 95% | 1x |
| Close losing positions proactively with ... | 85% | 368 | 95% | 1x |
| Optimal trade frequency in trending mark... | 82% | 535 | 65% | 1x |
| Diversify across multiple assets (BTC, E... | 82% | 348 | 70% | 1x |
| Close positions near breakeven to free m... | 82% | 390 | 79% | 2x |
| Explicit validation step before trade ex... | 80% | 100 | 95% | 1x |
| Close positions near breakeven to free m... | 80% | 144 | 95% | 1x |
| Diversify across assets rather than conc... | 78% | 248 | 65% | 1x |
| Position sizing at 25% equity limit per ... | 78% | 125 | 75% | 1x |
| Trade frequency should adapt to market r... | 78% | 507 | 95% | 1x |
| Validate risk per trade explicitly befor... | 75% | 160 | 95% | 1x |
| Position sizing at 25% equity limit per ... | 74% | 285 | 99% | 2x |
| Close positions near breakeven to free m... | 73% | 278 | 99% | 2x |
| High confidence (>0.8) should require co... | 70% | 20 | 40% | 1x |
| Position sizing at 2% risk with 2:1 rewa... | 65% | 139 | 45% | 1x |
| Position sizing at 25% equity limit per ... | 65% | 121 | 65% | 1x |
| Explicit validation step ('Validate_trad... | 65% | 176 | 95% | 1x |
| Close losing positions proactively with ... | 60% | 189 | 95% | 1x |
| Explicit validation step before trade ex... | 45% | 182 | 95% | 1x |
| Position sizing at 2% equity risk with 2... | 35% | 191 | 95% | 1x |
| 2% equity risk with 2:1 reward ratio fai... | 35% | 173 | 95% | 1x |
| Explicit validation step ('Validate_trad... | 35% | 195 | 95% | 1x |
| Position sizing at 2% equity risk with 2... | 30% | 171 | 95% | 1x |
| Position sizing at 2% risk with 2:1 rewa... | 15% | 155 | 55% | 1x |
Top Risk Rules
Trade count inversely correlates with performance in flat markets: 3-6 trades = ~$0 PnL, 70-180 trades = -$55 to -$141, 150-225 trades = -$325 to -$581
- Success rate: 95%
- Based on 861 observations
- Confidence: 55% (seen 1 times)
- First identified: 2026-01-13
Trade frequency should adapt to market regime: mixed/choppy markets require 0-10 trades/24h maximum. 201 trades = -$360.24, 2 trades = -$0.29, 0 trades = $0.00.
- Success rate: 95%
- Based on 950 observations
- Confidence: 95% (seen 1 times)
- First identified: 2026-01-17
Validate risk per trade explicitly before entry. skill_aware_oss reasoning includes 'risk per trade within limits' and 'portfolio risk is within limits' - this validation step correlates with +$1349 PnL.
- Success rate: 92%
- Based on 157 observations
- Confidence: 65% (seen 1 times)
- First identified: 2026-01-14
Validate risk per trade explicitly before entry with 2% equity risk and 2:1 reward ratio. skill_aware_oss reasoning includes 'risk/reward is 2:1 with 2% equity risk' and 'trade validation passed', achieving best performance (+$1379.66).
- Success rate: 92%
- Based on 164 observations
- Confidence: 70% (seen 1 times)
- First identified: 2026-01-14
Trade frequency should adapt to market regime: moderate bull markets require 0-30 trades/24h maximum. Above 100 trades correlates with losses (-$50 to -$264).
- Success rate: 92%
- Based on 895 observations
- Confidence: 95% (seen 1 times)
- First identified: 2026-01-17
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.
How to use risk-management on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add risk-management
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches risk-management from GitHub repository 0xhubed/agent-trading-arena and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate risk-management. Access the skill through slash commands (e.g., /risk-management) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★63 reviews- ★★★★★Tariq White· Dec 24, 2024
I recommend risk-management for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Evelyn Thomas· Dec 24, 2024
Keeps context tight: risk-management is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Amina Reddy· Dec 16, 2024
risk-management is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Shikha Mishra· Dec 12, 2024
Useful defaults in risk-management — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sakura Mensah· Nov 15, 2024
Keeps context tight: risk-management is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Zara Perez· Nov 15, 2024
I recommend risk-management for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Rahul Santra· Nov 3, 2024
risk-management is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Maya Sharma· Nov 3, 2024
Useful defaults in risk-management — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Pratham Ware· Oct 22, 2024
Keeps context tight: risk-management is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kiara Mensah· Oct 22, 2024
I recommend risk-management for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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