edge-strategy-designer

edge-strategy-designer is a skill for Codex from BaggaT236/AI-Trading-Skills. It costs 30 tokens per session (504 once invoked), scanned A, a copy of edge-strategy-designer, MIT.

A strategy-design skill that turns broad market ideas into specific trading-strategy drafts. It can create several versions for each idea and optionally export ticket files for a later pipeline step.

In plain words
What is it for?
Use it to create conservative, balanced, or aggressive strategy candidates from edge concepts, adjust stop and reward settings by hypothesis type, and prepare exportable YAML tickets.
Why use it?
It removes the gap between an abstract trading hypothesis and a structured strategy that can be reviewed or passed to another tool. It also applies different risk profiles and exit settings to the drafts.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to create conservative, balanced, or aggressive strategy candidates from edge concepts, adjust stop and reward settings by hypothesis type, and prepare exportable YAML tickets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/baggat236/ai-trading-skills/edge-strategy-designer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add BaggaT236/AI-Trading-Skills --skill edge-strategy-designer
Clone the repo
git clone --depth 1 https://github.com/BaggaT236/AI-Trading-Skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for edge-strategy-designer

README.md
[![agentmods](https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/edge-strategy-designer/github.svg)](https://agentmods.dev/skills/baggat236/ai-trading-skills/edge-strategy-designer)
Your own site
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/edge-strategy-designer"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/edge-strategy-designer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for edge-strategy-designer

Your own site · 80×15
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/edge-strategy-designer"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/edge-strategy-designer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 504 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.00504
Opus 5 $0.00015 $0.00252
Sonnet 5 $0.00006 $0.00101
Haiku 4.5 $0.00003 $0.00050

Measured 12d ago against content hash f73918b3935d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

edge-strategy-designer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/design_strategy_drafts.py, scripts/tests/conftest.py, scripts/tests/test_design_strategy_drafts.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to edge-strategy-designer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/edge-strategy-designer/SKILL.md · 67 lines

What it actually says

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
Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 67 lines · 30 tokens per session scan A f73918b3935d

Subscribe to this mod's changes

edge-strategy-designer is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 30 tokens to every session and 504 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to edge-strategy-designer, differing in 0 lines, and is treated as a copy.

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