strategy-pivot-designer

Q: How do I install strategy-pivot-designer?

Run npx skills add https://github.com/tradermonty/claude-trading-skills --skill strategy-pivot-designer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/strategy-pivot-designer/ (personal) or .claude/skills/strategy-pivot-designer/ (project).

by tradermontyFrontend & Design

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

Installs: 3.4K
Last 24h: +19
Trending rank: #6210
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/tradermonty/claude-trading-skills --skill strategy-pivot-designer

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads strategy-pivot-designer automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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

Accumulate backtest evaluation results into an iteration history file using --append-eval.
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.
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.
Review ranked proposals (scored by quality potential + novelty).
For exportable proposals, ticket YAML is ready for edge-candidate-agent pipeline.
For research_only proposals, manual strategy design needed before pipeline integration.
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

FAQ

What does the strategy-pivot-designer skill do?

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

How do I install strategy-pivot-designer?

Run npx skills add https://github.com/tradermonty/claude-trading-skills --skill strategy-pivot-designer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/strategy-pivot-designer/ (personal) or .claude/skills/strategy-pivot-designer/ (project).

Which AI agents can use strategy-pivot-designer?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is strategy-pivot-designer safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains strategy-pivot-designer?

It is published by tradermonty in tradermonty/claude-trading-skills. It has 3,354 recorded installs.