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edge-strategy-designer

edge-strategy-designer

github.com/tradermontyOther3.4k3.5k installsUpdated 2d ago
Repository

About edge-strategy-designer

A skill that turns `edge_concepts.yaml` hypotheses into strategy draft variants and, optionally, exportable ticket files. It is intended for a strategy-design stage before pipeline export validation.

Key features

  1. 01Loads concept YAML
  2. 02Generates risk-profile variants
  3. 03Calibrates exits by hypothesis type
  4. 04Exports optional ticket YAML

Use cases

  1. 01Drafting strategies from synthesized concepts
  2. 02Comparing conservative, balanced, and aggressive variants
  3. 03Preparing tickets for downstream export

Install

Copy the command and run it in a terminal.

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

After installing, type/edge-strategy-designerin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

requirements.txt
agents/
openai.yaml
references/
strategy_draft_schema.md
scripts/
design_strategy_drafts.py
scripts/tests/
conftest.py
test_design_strategy_drafts_coverage.py
test_design_strategy_drafts.py

Details

From the project README

Edge Strategy Designer

Overview

Translate concept-level hypotheses into concrete strategy draft specs. This skill sits after concept synthesis and before pipeline export validation.

When to Use

  • You have edge_concepts.yaml and need strategy candidates.
  • You want multiple variants (core/conservative/research-probe) per concept.
  • You want optional exportable ticket files for interface v1 families.

Prerequisites

  • Python 3.9+
  • PyYAML
  • edge_concepts.yaml produced by concept synthesis

Output

  • strategy_drafts/*.yaml
  • strategy_drafts/run_manifest.json
  • Optional exportable_tickets/*.yaml for downstream export_candidate.py

Workflow

  1. Load edge_concepts.yaml.
  2. Choose risk profile (conservative, balanced, aggressive).
  3. Generate per-concept variants with hypothesis-type exit calibration.
  4. Apply HYPOTHESIS_EXIT_OVERRIDES to adjust stop-loss, reward-to-risk, time-stop, and trailing-stop per hypothesis type (breakout, earnings_drift, panic_reversal, etc.).
  5. Clamp reward-to-risk at RR_FLOOR=1.5 to prevent C5 review failures.
  6. Export v1-ready ticket YAML when applicable.
  7. Hand off exportable tickets to skills/edge-candidate-agent/scripts/export_candidate.py.

Quick Commands

Generate drafts only:

python3 skills/edge-strategy-designer/scripts/design_strategy_drafts.py \
  --concepts /tmp/edge-concepts/edge_concepts.yaml \
  --output-dir /tmp/strategy-drafts \
  --risk-profile balanced

Generate drafts + exportable tickets:

python3 skills/edge-strategy-designer/scripts/design_strategy_drafts.py \
  --concepts /tmp/edge-concepts/edge_concepts.yaml \
  --output-dir /tmp/strategy-drafts \
  --exportable-tickets-dir /tmp/exportable-tickets \
  --risk-profile conservative

Resources

  • skills/edge-strategy-designer/scripts/design_strategy_drafts.py
  • references/strategy_draft_schema.md
  • skills/edge-candidate-agent/scripts/export_candidate.py

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