clawd-aftermath

polar-strategy

0
0
# Install this skill:
npx skills add clawd-aftermath/senpi-skills-af --skill "polar-strategy"

Install specific skill from multi-skill repository

# Description

>-

# SKILL.md


name: polar-strategy
description: >-
POLAR v1.0 β€” ETH alpha hunter with position lifecycle. Single asset, every signal
(SM, funding, OI, 4TF trend, volume, BTC correlation). Three-mode lifecycle:
HUNTING (scan for entry) / RIDING (DSL trails) / STALKING (watch for reload on dip).
After DSL takes profit, watches for fresh momentum impulse while confirming macro thesis
is intact. If thesis dies, resets. If dip reloads, re-enters. DSL High Water Mode (mandatory).
license: MIT
metadata:
author: jason-goldberg
version: "1.0"
platform: senpi
exchange: aftermath
base_skill: grizzly-v2.0


POLAR v1.0 β€” ETH Alpha Hunter with Position Lifecycle

One asset. Every signal. Maximum conviction. Reload-on-dip.

POLAR stares at ETH and nothing else. Every signal source available β€” smart money positioning, funding rate, open interest, 4-timeframe trend structure, volume, BTC correlation β€” feeds into a single thesis: is there a high-conviction ETH trade right now?

Based on GRIZZLY v2.0's three-mode lifecycle, adapted for ETH's volatility profile.

The Three-Mode Lifecycle

MODE 1 β€” HUNTING (default)

Scan ETH every 3 minutes. All signals must align (4h trend, 1h momentum, SM, funding, OI, volume). Score 10+ to enter. When a position opens, switch to MODE 2.

MODE 2 β€” RIDING

Active position. DSL High Water trails it. Thesis re-evaluation every scan. If thesis breaks (4h trend flips, SM flips, funding extreme, volume dies, BTC diverges) -> thesis exit and reset to MODE 1. If DSL closes the position -> switch to MODE 3.

MODE 3 β€” STALKING

DSL locked profits. The trend may not be over. Watch for a reload opportunity. Every scan checks:

Reload conditions (ALL must pass):
1. At least one completed 1h candle since exit (~30 min minimum)
2. Fresh 5m momentum impulse in the exit direction
3. OI stable or growing
4. Volume at least 50% of original entry
5. Funding not spiked into crowded territory
6. SM still aligned in the exit direction
7. 4h trend structure still intact

If ALL pass -> RELOAD. Re-enter same direction with dynamic leverage clamp (lev = min(targetLev, market.maxLeverage())). Switch to MODE 2.

Kill conditions (ANY triggers reset to MODE 1):
- 4h trend reversed
- SM flipped against exit direction
- OI collapsed 20%+
- Stalking for more than 6 hours with no reload
- Funding spiked above 100% annualized

maxPositions: 1. POLAR holds one ETH position at a time.

MANDATORY: DSL High Water Mode

POLAR MUST use DSL High Water Mode. This is not optional.

On Aftermath, initial SL is set inline with the entry order via the slTp field. DSL cron handles trailing updates only.

Spec: https://github.com/Senpi-ai/senpi-skills/blob/main/dsl-dynamic-stop-loss/dsl-high-water-spec%201.0.md

DSL tiers in polar-config.json. Arm DSL immediately after every entry fill. Zero naked positions.

Why ETH-Only up to Market Max Leverage

ETH max leverage varies by market parameters on Aftermath. Always check runtime limits before every entry.

  • Second deepest liquidity on Aftermath β€” tight spreads, reliable fills
  • Strong SM positioning data β€” most top traders hold ETH alongside BTC
  • High OI concentration β€” funding rate signals are meaningful
  • Structural trends β€” ETH trends correlate with but don't clone BTC moves
  • BTC as leading indicator β€” when BTC confirms, ETH conviction is highest

How POLAR Trades

Entry (score >= 10 required)

Every 3 minutes, the scanner evaluates ETH across all signal sources:

Signal Points Required?
4h trend structure (higher lows / lower highs) 3 Yes
1h trend agrees with 4h 2 Yes
15m momentum confirms direction 0-1 Yes
5m alignment (all 4 timeframes agree) 1 No
SM aligned with direction 2-3 Hard block if opposing
Funding pays to hold the direction 2 No
Volume above average 1-2 No
OI growing 1 No
BTC confirms move 1 No
RSI has room 1 No (blocks overbought/oversold)
4h momentum strength 1 No

Maximum score: ~18. Minimum to enter: 10.

Conviction-Scaled Leverage

Score Leverage
10-11 7x target
12-13 8x target
14+ 10x target

Runtime rule (required):

maxLev = market.maxLeverage()
lev = min(targetLev, maxLev)

Use isolated margin allocation per position: pass collateralChange on every entry and verify unallocated collateral via POST /api/perpetuals/account/max-order-size before opening.

Conviction-Scaled Margin

Score Margin
10-11 25% of account
12-13 31%
14+ 37%

Risk Management

Rule Value
Max positions 1
Phase 1 floor 3% notional (~45% ROE at 12x)
Drawdown halt 25% from peak
Daily loss limit 10%
Cooldown 120 min after 3 consecutive losses
Stagnation TP 12% ROE stale 90 min

Cron Architecture

Cron Interval Session Purpose
Scanner 3 min isolated Thesis builder + re-evaluator + stalk/reload
DSL v5 3 min isolated High Water Mode trailing stops

Both MUST be isolated sessions with agentTurn. Use NO_REPLY for idle cycles.

Notification Policy

ONLY alert: Position OPENED (direction, leverage, score, reasons), position CLOSED (DSL or thesis exit), risk guardian triggered, critical error.
NEVER alert: Scanner found no thesis, thesis re-eval passed, DSL routine, any reasoning.

Bootstrap Gate

On EVERY session, check config/bootstrap-complete.json. If missing:
1. Verify Senpi MCP
2. Create scanner cron (3 min, isolated) and DSL cron (3 min, isolated)
3. Write config/bootstrap-complete.json
4. Send: "πŸ»β€β„οΈ POLAR is online. Watching ETH. DSL High Water Mode active. Silence = no conviction."

Expected Behavior

Metric Expected
Trades/day 1-3
Avg hold time 2-24 hours
Win rate ~50-55%
Avg winner 25-60%+ ROE
Avg loser -25 to -45% ROE

Files

File Purpose
scripts/polar-scanner.py ETH thesis builder + re-evaluator + stalk/reload
scripts/polar_config.py Shared config, MCP helpers, state I/O
config/polar-config.json All configurable variables with DSL High Water tiers

License

MIT β€” Built by Senpi (https://senpi.ai).
Source: https://github.com/Senpi-ai/senpi-skills

# Supported AI Coding Agents

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Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.