strategy-pivot-designer

name: strategy-pivot-designerdescription: Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

Strategy Pivot Designer

Overview

Detect when a strategy's backtest iteration loop has stalled and propose structurally different strategy architectures. This skill acts as the feedback loop for the Edge pipeline (hint-extractor -> concept-synthesizer -> strategy-designer -> candidate-agent), breaking out of local optima by redesigning the strategy's skeleton rather than tweaking parameters.

When to Use

• Backtest scores have plateaued despite multiple refinement iterations.
• A strategy shows signs of overfitting (high in-sample, low robustness).
• Transaction costs defeat the strategy's thin edge.
• Tail risk or drawdown exceeds acceptable thresholds.
• You want to explore fundamentally different strategy architectures for the same market hypothesis.

Prerequisites

• Python 3.9+
• PyYAML
• Iteration history JSON (accumulated backtest-expert evaluations)
• Source strategy draft YAML (from edge-strategy-designer)

Output

• pivot_drafts/research_only/*.yaml — strategy_draft compatible YAML proposals
• pivot_drafts/exportable/*.yaml — export-ready drafts + ticket YAML for candidate-agent
• pivot_report_*.md — human-readable pivot analysis
• pivot_manifest_*.json — metadata for all generated files
• pivot_diagnosis_*.json — stagnation detection results

Workflow

1. Accumulate backtest evaluation results into an iteration history file using --append-eval.
2. Run stagnation detection on the history to identify triggers (plateau, overfitting, cost defeat, insufficient profit factor, tail risk). A no-loss profit factor is not cost defeat; an undefined or overflowed ratio requires review.
3. If the diagnosis says review_required, repair or re-evaluate the underlying metrics first; do not generate pivots. If stagnation is confirmed, generate pivot proposals using three techniques: assumption inversion, archetype switch, objective reframe.
4. Review ranked proposals (scored by quality potential + novelty).
5. For exportable proposals, ticket YAML is ready for edge-candidate-agent pipeline.
6. For research_only proposals, manual strategy design needed before pipeline integration.
7. Feed the selected pivot draft back into backtest-expert for the next iteration cycle.

Quick Commands

Append a backtest evaluation to history (creates history if new):

python3 skills/strategy-pivot-designer/scripts/detect_stagnation.py \
  --append-eval reports/backtest_eval_2026-02-10_120000.json \
  --history reports/iteration_history.json \
  --strategy-id draft_edge_concept_breakout_behavior_riskon_core \
  --changes "Widened stop_loss from 5% to 7%"

Detect stagnation:

python3 skills/strategy-pivot-designer/scripts/detect_stagnation.py \
  --history reports/iteration_history.json \
  --output-dir reports/

Generate pivot proposals:

python3 skills/strategy-pivot-designer/scripts/generate_pivots.py \
  --diagnosis reports/pivot_diagnosis_*.json \
  --strategy reports/edge_strategy_drafts/draft_*.yaml \
  --max-pivots 3 \
  --output-dir reports/

Resources

• skills/strategy-pivot-designer/scripts/detect_stagnation.py
• skills/strategy-pivot-designer/scripts/generate_pivots.py
• references/stagnation_triggers.md
• references/strategy_archetypes.md
• references/pivot_techniques.md
• references/pivot_proposal_schema.md
• skills/backtest-expert/scripts/evaluate_backtest.py
• skills/edge-strategy-designer/scripts/design_strategy_drafts.py