emerging-movers▌
senpi-ai/senpi-skills · updated Apr 8, 2026
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Tracks Smart Money market concentration across all Hyperliquid assets and flags assets accelerating up the ranks before they become crowded top-3 plays. By the time an asset hits the top of the SM leaderboard, the easy money is gone. This catches the trajectory.
Emerging Movers Detector v3.1
Tracks Smart Money market concentration across all Hyperliquid assets and flags assets accelerating up the ranks before they become crowded top-3 plays. By the time an asset hits the top of the SM leaderboard, the easy money is gone. This catches the trajectory.
One API call per scan. Near-zero LLM tokens. Runs every 60 seconds.
How It Works
The SM Profit Concentration Leaderboard
Senpi's leaderboard_get_markets returns all assets ranked by percentage of total Smart Money profit in the last 4-hour rolling window. This isn't trader count — it's where the money is actually flowing.
#1 ETH SHORT 31.4% 286 traders
#2 BTC SHORT 25.1% 436 traders
#3 HYPE SHORT 24.2% 330 traders
...
#36 ASTER SHORT 0.2% 18 traders ← 60s later: #13, 0.82%, 65 traders
The script tracks this leaderboard over time and detects acceleration.
Detection Signals
Immediate Action Signals (v3+)
| Signal | Condition | Priority |
|---|---|---|
| IMMEDIATE_MOVER | 10+ rank jump from #25+ in ONE scan | Highest — act now |
| NEW_ENTRY_DEEP | Appears in top 20 from nowhere | Very high |
| CONTRIB_EXPLOSION | 3x+ contribution increase in one scan | Very high |
| DEEP_CLIMBER | 5+ rank jump from #25+ | High |
Trend Signals
| Signal | Condition |
|---|---|
| NEW_ENTRY | First appearance in top 50 |
| RANK_UP | Jumped 2+ positions in one scan |
| CLIMBING | 3+ positions up over several scans |
| ACCEL | Contribution % increasing scan-over-scan |
| STREAK | Consistently climbing every check |
| VELOCITY | Sustained positive contribution growth |
v3.1 Quality Filters
These prevent false IMMEDIATE signals that looked great on rank jump alone but failed on execution:
| Filter | Rule | Rationale |
|---|---|---|
| Erratic rank | >5 rank reversals in history → erratic: true, downgraded |
Bouncing ranks are noise |
| Velocity gate | contribVelocity < 0.03 → lowVelocity: true, excluded from IMMEDIATE |
No momentum behind the move |
| Trader count floor | <10 traders → SKIP IMMEDIATE | Single whale risk |
| Max leverage check | max leverage < 10x → SKIP | Not worth the limited position sizing |
See references/quality-filters.md for implementation details and real-world examples.
Architecture
┌────────────────────────────────────┐
│ Cron: every 60 seconds │
├────────────────────────────────────┤
│ scripts/emerging-movers.py │
│ • Loads scan history from JSON │
│ • Fetches leaderboard (1 API call) │
│ • Parses top 50 markets │
│ • Compares with previous scans │
│ • Detects signals + v3.1 filters │
│ • Saves updated history │
│ • Outputs JSON with alerts │
├────────────────────────────────────┤
│ Agent reads output: │
│ • IMMEDIATE alerts → evaluate now │
│ • Deep climbers → queue for review │
│ • No alerts → silent │
└────────────────────────────────────┘
Files
| File | Purpose |
|---|---|
scripts/emerging-movers.py |
Scanner script |
emerging-movers-history.json |
Auto-managed scan history (last 60 scans) |
max-leverage.json |
Optional: asset max leverage reference |
Output
See references/output-schema.md for the complete JSON schema.
Key top-level fields: alerts[], topMovers[], immediateMovers[], deepClimbers[], scanCount, timestamp.
Per-alert fields: asset, direction, rank, prevRank, contribution, traderCount, reasons[], contribVelocity, isImmediate, isDeepClimber, erratic, lowVelocity.
Cron Setup
*/1 * * * * python3 scripts/emerging-movers.py
Agent Response Logic
isImmediate: true+erratic: false+lowVelocity: false→ Evaluate immediately for entry via ScannerisDeepClimber: true→ Queue for next scanner runerratic: trueorlowVelocity: true→ Log but do not act- No alerts → Silent
Companion skills
- opportunity-scanner — use Scanner to deep-dive assets flagged by Emerging Movers
- autonomous-trading — full loop integrating Emerging Movers as entry trigger
- wolf-strategy — uses IMMEDIATE_MOVER as primary entry signal
How to use emerging-movers 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 emerging-movers
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches emerging-movers from GitHub repository senpi-ai/senpi-skills 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 emerging-movers. Access the skill through slash commands (e.g., /emerging-movers) 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
Submit your Claude Code skill and start earning
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★★★★★41 reviews- ★★★★★Diya Bansal· Dec 28, 2024
emerging-movers has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Zara Bansal· Dec 28, 2024
emerging-movers reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Shikha Mishra· Dec 20, 2024
Keeps context tight: emerging-movers is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Zara Agarwal· Dec 8, 2024
I recommend emerging-movers for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ira Taylor· Nov 27, 2024
emerging-movers reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Diya Thomas· Nov 19, 2024
emerging-movers fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Dev Torres· Nov 19, 2024
I recommend emerging-movers for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Soo Liu· Nov 19, 2024
Keeps context tight: emerging-movers is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kiara Nasser· Oct 18, 2024
Registry listing for emerging-movers matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Henry Chen· Oct 10, 2024
We added emerging-movers from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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