Give your agent a budget, a target, and a deadline — then let it trade. The agent creates a strategy wallet, scans for opportunities, opens positions, protects profits with DSL, and enforces risk controls.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionautonomous-tradingExecute the skills CLI command in your project's root directory to begin installation:
Fetches autonomous-trading from senpi-ai/senpi-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate autonomous-trading. Access via /autonomous-trading in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Give your agent a budget, a target, and a deadline — then let it trade. The agent creates a strategy wallet, scans for opportunities, opens positions, protects profits with DSL, and enforces risk controls.
When creating a strategy, include skill_name and skill_version in the call. See references/skill-attribution.md for details.
Install these companion skills first:
Minimum budget: $500 (recommend $1k+)
See references/bugs-and-gotchas.md — critical issues from live trading including the dryRun bug, phantom closes, XYZ DEX margin type, Tier 1 lock misconception, and scanner leverage vs actual max.
Collect: budget, target, deadline, risk tolerance (conservative/moderate/aggressive), asset preferences.
See references/risk-rules.md for complete risk rules by profile.
v6 Core Rules:
The #1 Rule — Hourly Trend Alignment. ALL trades must confirm with hourly candle structure. Counter-trend = hard skip, no exceptions. This single rule prevents the majority of losing trades.
Max Leverage Check. Always check max-leverage.json before entering. Scanner leverage is conservative, not actual max.
Concentration Over Diversification. At small account sizes ($500-$10k), 2-4 high-conviction positions beat 6 mediocre ones. Cross-margin math: 4 positions → 80.6% margin buffer, 2 positions → 89.7%.
Every Slot Must Maximize ROI. Empty slot > mediocre position. If a position isn't working, cut it and free the slot.
Speed Filter. Best moves happen FAST (XRP hit Tier 3 in 19 min, XMR Tier 2 in 37 min). Slow movers are suspects.
Before opening, check total LONG vs SHORT notional. Cap at 70% in one direction.
| Scanner Score | Position Size |
|---|---|
| 250+ | Up to max per-position |
| 200-250 | 75% of max |
| 175-200 | 50% of max |
| < 175 | Skip |
strategy_create_strategy(budgetUsd, leverageType, riskLabel)
Returns strategyId + walletAddress. Fund the wallet.
JSON config tracking: risk profile, position limits, score thresholds, active positions, trade journal. See references/playbook-schema.md.
Race Condition Prevention (v6 — CRITICAL)
Multiple cron jobs (scanner, SM flip, DSL) can all try to close the same position. When ANY job closes a position:
# 1. Close the position
result = close_position(wallet, asset)
# 2. Immediately deactivate DSL state file
state["active"] = False
save_state(state)
# 3. Disable DSL cron for this asset
disable_cron(f"dsl-{asset}")
All three steps MUST happen in the same action. This prevents phantom closes.
Cron Schedule:
| Job | Interval | Purpose |
|---|---|---|
| Opportunity Scanner | 10-30 min (time-aware) | Find setups |
| DSL Monitor | 2-3 min per position | Trailing stops |
| SM Flip Detector | 5 min | Conviction changes |
| Portfolio Update | 15 min | Reporting |
See references/cron-setup.md for detailed cron configuration, time-aware scheduling, and SM flip detection logic.
SCAN → EVALUATE → TRADE → PROTECT → REPEAT
For each scan result:
1. Check hourly trend alignment (HARD REQUIREMENT)
2. Check directional exposure guard
3. Check max leverage via max-leverage.json
4. Score ≥ 175? → Size by score tier
5. Open position → Create DSL state → Start DSL cron
6. Journal the trade (scanner snapshot at entry)
| Condition | Action |
|---|---|
| SM conviction drops 4→1 (e.g., 220→24 traders in 10 min) | Cut immediately |
| Dead weight at conviction 0 | Cut immediately — free the slot |
| Position stagnant, better opportunity available | Rotate |
Hard Stops (automatic):
What the Agent Should NEVER Do:
See references/lessons.md for what works, what doesn't, retrace tuning, and fee awareness from live trading.
See references/api-tools.md for the key Senpi tools used by this skill.
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
huynguyen03dev/xauusd-trading
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
autonomous-trading fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
autonomous-trading fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
autonomous-trading is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
autonomous-trading has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added autonomous-trading from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for autonomous-trading matched our evaluation — installs cleanly and behaves as described in the markdown.
autonomous-trading fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
autonomous-trading is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
autonomous-trading is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
autonomous-trading is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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