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Business · Data Analysis / AGENT SKILL
strategy-pivot-designer
0
Detects stalled backtest iterations and proposes structurally different trading strategies.
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
Understand the trade-offs.
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Original instructions from the publisher’s SKILL.md
# 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, tail risk). 3. If stagnation detected, 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): ```bash 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: ```bash python3 skills/strategy-pivot-designer/scripts/detect_stagnation.py \ --history reports/iteration_history.json \ --output-dir reports/ ``` Generate pivot proposals: ```bash 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`