Edge Strategy Designer
Convert abstract edge concepts into strategy draft variants and optional exportable ticket YAMLs for edge-candidate-agent export/validation.
No API
Download Skill Package (.skill) View Source on GitHub
Table of Contents
1. Overview
Translate concept-level hypotheses into concrete strategy draft specs. This skill sits after concept synthesis and before pipeline export validation.
2. When to Use
- You have
edge_concepts.yamland need strategy candidates. - You want multiple variants (core/conservative/research-probe) per concept.
- You want optional exportable ticket files for interface v1 families.
3. Prerequisites
- Python 3.9+
PyYAMLedge_concepts.yamlproduced by concept synthesis
4. Quick Start
- Load
edge_concepts.yaml. - Choose risk profile (
conservative,balanced,aggressive). - Generate per-concept variants with hypothesis-type exit calibration.
- Apply
HYPOTHESIS_EXIT_OVERRIDESto adjust stop-loss, reward-to-risk, time-stop, and trailing-stop per hypothesis type (breakout, earnings_drift, panic_reversal, etc.). - Clamp reward-to-risk at
RR_FLOOR=1.5to prevent C5 review failures. - Export v1-ready ticket YAML when applicable.
- Hand off exportable tickets to
skills/edge-candidate-agent/scripts/export_candidate.py.
5. Workflow
- Load
edge_concepts.yaml. - Choose risk profile (
conservative,balanced,aggressive). - Generate per-concept variants with hypothesis-type exit calibration.
- Apply
HYPOTHESIS_EXIT_OVERRIDESto adjust stop-loss, reward-to-risk, time-stop, and trailing-stop per hypothesis type (breakout, earnings_drift, panic_reversal, etc.). - Clamp reward-to-risk at
RR_FLOOR=1.5to prevent C5 review failures. - Export v1-ready ticket YAML when applicable.
- Hand off exportable tickets to
skills/edge-candidate-agent/scripts/export_candidate.py.
6. Resources
References:
skills/edge-strategy-designer/references/strategy_draft_schema.md
Scripts:
skills/edge-strategy-designer/scripts/design_strategy_drafts.py