tradermonty/claude-trading-skills

strategy-pivot-designer

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

All-time #6375 Trending #5707 Hot #257 First seen Feb 27, 2026
8-week activity · all time api

Installation

$ npx skills add tradermonty/claude-trading-skills --skill strategy-pivot-designer

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 2.8K
License LICENSE
Default branch main
Open issues 31
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,431 B
  • docs SUMMARY.md 175 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1,914 installs

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

  • pivotdrafts/researchonly/*.yaml — strategy_draft compatible YAML proposals
  • pivot_drafts/exportable/*.yaml — export-ready drafts + ticket YAML for candidate-agent
  • pivotreport*.md — human-readable pivot analysis
  • pivotmanifest*.json — metadata for all generated files
  • pivotdiagnosis*.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):

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/pivotproposalschema.md
  • skills/backtest-expert/scripts/evaluate_backtest.py
  • skills/edge-strategy-designer/scripts/designstrategydrafts.py