Albatross Strategy

🐦‍⬛ ALBATROSS v1.0.0 — Multi-week Arena Conviction Mirror

Mirror the consistent winners, not the lucky-week winners. Albatross selects Arena leaders by a composite score that rewards multi-week persistence and penalizes one-shot lucky weeks.

Why this strategy exists

The Senpi Arena resets every Thursday. A trader can post a +98% weekly ROE from one good week and three flat weeks — and they'll top the leaderboard, but mirroring them is a survivor-bias trap.

Albatross corrects for this by pulling 4 weekly snapshots + 1 monthly snapshot and ranking by a composite that respects both magnitude and consistency:

conviction = 0.3 × monthly_roe
            + 0.7 × mean(weekly_roe across last 4 weeks)
            − 0.5 × stdev(weekly_roe)

A trader posting +30%/+25%/+20%/+15% across 4 weeks (mean +22.5%, stdev ±5.6%) scores conviction ≈ 14.0. A trader posting +98%/0%/-5%/-3% (mean +22.5%, stdev ±42.5%) scores conviction ≈ -5.8 despite the same mean. Albatross rejects the second; mirrors the first.

CRITICAL RULES

RULE 1: REQUIRES USER-SCOPE AUTH TOKEN

Service tokens cannot resolve other users' strategy wallets or call discovery_get_trader_state for other addresses. Both gate on user identity. The operator must provide a Privy-issued Senpi user token via SENPI_AUTH_TOKEN, not an MCP service key.

RULE 2: Producer mirrors. DSL exits.

The producer detects when a leader opens a NEW position (diff against last-tick snapshot in state/leader-positions/) and emits one signal per detection. The runtime opens via FEEOPTIMIZEDLIMIT. The DSL Phase 1 max_loss + Phase 2 wide ratchet manages exits.

RULE 3: Leader pool refreshes every 4h, not every tick

Pulling 4 weekly leaderboards + 1 monthly on every 300s tick would burn MCP quota. The pool is cached in state/leader-pool.json with a leaderRefreshHours TTL (default 4). Only the per-leader position snapshots refresh per tick.

RULE 4: Exclude betashop xHandle by default

Senpi's own fleet agents (Bison12, Cheetah, Jaguar2, etc.) often top the Arena. Mirroring them creates a feedback loop — Albatross would just be a slower copy of those agents. Config excludeXHandles: ["betashop"] filters them out. Operators can add other handles to skip.

RULE 5: 96h hard timeout cap

We don't have visibility into the leader's exit logic. Hard timeout 96h (4 days) frees the slot if the position drifts without resolution. Phase 1 max_loss 20% catches catastrophic adverse moves; Phase 2 wide ladder lets winners run within the 96h window.

How Albatross composes its leader pool

1. Pull arena_leaderboard(period_type=WEEK, qualified=true) for the current week + last 3 weeks.
2. Pull arena_leaderboard(period_type=MONTH, qualified=true) for the current month.
3. For each unique senpiUserId across those 5 calls:

• Compute mean(weekly_roe) and stdev(weekly_roe) across the weeks the trader appeared.
• Look up monthly_roe (default 0 if absent).
• conviction = 0.3 × monthly + 0.7 × weekly_mean − 0.5 × weekly_stdev.

1. Filter to traders with:

• conviction > 0 (no negative-expectation leaders)
• weeks_traded >= 3 (default, ensures persistence)
• Each week's notionalVolume >= 50000 (default, no toy accounts)
• xHandle != "betashop" (no Senpi fleet self-mirror)

1. Top N by conviction → pool (default 5).

How Albatross detects new positions

Per tick (every 300s):

1. For each leader in the pool, call strategy_list({userIds: [senpiUserId], status: ["ACTIVE"]}) → list of strategy wallet addresses.
2. Call discovery_get_trader_state(trader_addresses=wallets, latest=true) → current open positions.
3. Compare to last-tick snapshot in state/leader-positions/.json. Detect coins/directions present now but not in last snapshot.
4. For each NEW position: emit ALBATROSS_ARENA_MIRROR signal with asset, direction, our sized marginUsd, and our capped leverage.

Mirror logic — what we copy and what we adapt

| Field | Adapt | |---|---| | Asset | Copy exactly (BTC, ETH, NVDA, BRENTOIL, whatever they opened) | | Direction | Copy exactly | | Leverage | Cap at config.leverage (default 5x, max 5x) — we don't follow into 25x leverage | | Sizing | Fixed marginPct * accountValue (default 15%) — we don't size proportional to their conviction | | Order type | FEEOPTIMIZEDLIMIT, maker-first 30s ALO | | TP/SL | Skip theirs, use our DSL |

Risk guardrails (runtime.yaml risk.guard_rails)

| Gate | Setting | Why | |---|---|---| | maxentriesperday | 5 | Multiple leaders fire — give the producer room | | perassetcooldownminutes | 120 | Don't re-mirror same asset within 2h | | dailylosslimitpct | 15 | Cap a bad day | | maxconsecutivelosses | 4 | Halt if leader pool is wrong for current regime | | cooldownminutes (post-loss) | 30 | Cool off briefly | | drawdownhaltpct | 20 | Catastrophic floor | | drawdownresetondayrollover | false | No grace |

Scanner pattern

This strategy uses the Trader follower (Jackal family) scanner pattern with multi-week selection — see senpi-trading-runtime/references/producer-patterns.md for the canonical reference. Primary MCP calls: arena_leaderboard (×5 for pool composition), strategy_list (per-leader wallet resolution), discovery_get_trader_state (per-leader position fetch).

Operator install

See [README.md](README.md). Pay close attention to RULE 1 — service tokens will not work.

Changelog

v1.0.0 (2026-05-20) — initial release

First multi-week Arena conviction mirror. Composite score weighting (0.3 monthly + 0.7 weeklymean − 0.5 weeklystdev) replaces the naive "mirror this week's #1" approach. Default pool size 5, refresh every 4h, max 5 entries/day.

License

MIT — Copyright 2026 Senpi (https://senpi.ai).

Skill Attribution

When creating a strategy, include skill_name and skill_version in the call. See references/skill-attribution.md for details.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Senpi-ai
• Source: Senpi-ai/senpi-skills
• License: MIT

Install and usage instructions live in the source repository linked above.