lynx-strategy

name: lynx-strategy description: >- LYNX v1.0.0 — Adaptive MIN_SCORE Self-Tuner. The Vulture v4.1 story productized into a first-class agent pattern. Runs a simple BTC/ETH/SOL/HYPE momentum scorer; every 6h pulls its own closed-trade history via audit_query, buckets trades by score, and auto-raises MIN_SCORE if any bucket at-or-above the floor is bleeding. The same operation Vulture's agent ran by hand, but on a scheduled cron. NEW archetype #15: Self-tuning / adaptive-threshold agent. license: MIT metadata: author: jason-goldberg version: "1.0.0" platform: senpi exchange: hyperliquid requires: - senpi-trading-runtime>=1.1.0 - senpi_runtime_helpers

🐯 LYNX v1.0.0 — Adaptive MIN_SCORE Self-Tuner

The Vulture v4.1 story productized. Lynx is a momentum agent that audits its own closed-trade history every 6 hours and raises its own MIN_SCORE when low-conviction buckets bleed.

Why this strategy exists

When Vulture's autonomous agent ran the 30-trade audit that led to v4.1, it manually identified that Score 7–8 trades had been net-negative and raised MIN_SCORE 7→9 by hand. The fix worked. The question Lynx asks: why is that operation manual?

Lynx bakes the same operation into a scheduled cron. Every auditEverySec (default 6h), it:

1. Pulls its own closed-trade history via audit_query(user_ids=[senpiUserId], action_type="close", limit=auditLimit)
2. Parses the entry score from each trade's ai_reasoning field
3. Buckets trades by score and computes {n, avg_roe_pct, win_rate_pct} per bucket
4. Identifies the highest-scoring bucket at or above the current floor that has n >= minBucketN AND avg_roe_pct < bucketBleedThresholdPct
5. If found, recommends MIN_SCORE = that_bucket + 1 (capped at maxMinScore)
6. If the recommendation moves by at least the hysteresis (1), persists the new MIN_SCORE and logs the adjustment

This is the first fleet agent that modifies its own behavior based on its own trade history. The same loop the Vulture team ran by hand — but every 6 hours, automatically, on every Lynx instance.

CRITICAL RULES

RULE 1: Self-tuning is gated on senpiUserId

The audit requires audit_query with the operator's Senpi user ID. If config.senpiUserId is empty, Lynx still runs (using initialMinScore) but the audit is skipped and the tick output notes "no senpiUserId — self-tuning disabled". The operator can find their ID via user_get_me or arena_leaderboard.

RULE 2: Lynx never lowers its own MIN_SCORE

The should_update_threshold function only acts on raises (hysteresis ≥ +1). A floor that has worked won't be relaxed by a quiet period. Lynx ratchets up; it never ratchets down.

RULE 3: The cap is hard

maxMinScore (default 7) is an absolute ceiling. Even if every bucket up to 7 bleeds, Lynx won't go above 7 — at which point the operator should diagnose the underlying scoring logic rather than keep raising the floor.

RULE 4: Adjustments are logged forever

Each successful raise is appended to state.adjustments with timestamp, previous and new floor, bleeding-bucket evidence, and the audit's trade-count. The state file is the audit trail.

RULE 5: Producer NEVER closes

DSL owns exits. Lynx's innovation is in entry selection, not exit management — exits use the proven let_winners_run ladder.

How Lynx scores a trade

Composite of 4 components (max ~8):

Initial MIN_SCORE: 4 (permissive — gives the audit data to work with). Auto-tunes up to maxMinScore: 7. Operators see the current MIN_SCORE in every tick's output (currentMinScore field) — so they can watch Lynx learn live.

DSL preset (let_winners_run — momentum-class)

Standard momentum-class let-winners-run: max_loss 20%, retrace 12, 7d hard_timeout, no weak_peak_cut, Phase 2 ladder +10/0 → +20/25 → +35/50 → +60/70 → +100/85. The Lynx innovation is in entry, not exit.

Scanner pattern

NEW archetype #15: Self-tuning / adaptive-threshold agent — see senpi-trading-runtime/references/producer-patterns.md. Primary MCP calls: market_get_asset_data per whitelisted asset (the producer signature), leaderboard_get_markets (SM gate), audit_query (the self-tuning audit — every 6h). The pure functions (parse_score_from_reasoning, compute_bucket_stats, recommend_min_score, should_update_threshold, pct_move, trend_direction, lynx_score) are unit-tested in tests/test_signal.py.

Operator install

See README.md.

Changelog

v1.0.0 (2026-05-29) — initial release

First fleet agent to modify its own behavior based on its own trade history. Productizes the Vulture v4.1 manual cull as a scheduled audit. Introduces archetype #15 (self-tuning agent). 19/19 unit tests covering both the self-tuning logic (parse_score, compute_bucket_stats, recommend_min_score, should_update_threshold) and the scoring logic (pct_move, trend_direction, lynx_score). Taker-true entry, disown-safe launch.

License

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

Skill Attribution

When creating a strategy, include skill_name and skill_version. See references/skill-attribution.md.