# Edge Candidate Agent

Generate and prioritize US equity long-side edge research tickets from EOD...

- Repository: https://github.com/tradermonty/claude-trading-skills (3536 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add tradermonty/claude-trading-skills --skill edge-candidate-agent -g -a claude-code -y`
Codex: `npx skills add tradermonty/claude-trading-skills --skill edge-candidate-agent -g -a codex -y`
Cursor: `npx skills add tradermonty/claude-trading-skills --skill edge-candidate-agent -g -a cursor -y`
Gemini CLI: `npx skills add tradermonty/claude-trading-skills --skill edge-candidate-agent -g -a gemini-cli -y`

## Description

Generate and prioritize US equity long-side edge research tickets from EOD observations, then export pipeline-ready candidate specs for trade-strategy-pipeline Phase I. Use when users ask to turn hypotheses/anomalies into reproducible research tickets, convert validated ideas into `strategy.yaml` + `metadata.json`, or preflight-check interface compatibility (`edge-finder-candidate/v1`) before running pipeline backtests.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Edge Candidate Agent

## Overview

Convert daily market observations into reproducible research tickets and Phase I-compatible candidate specs.
Prioritize signal quality and interface compatibility over aggressive strategy proliferation.
This skill can run end-to-end standalone, but in the split workflow it primarily serves the final export/validation stage.

## When to Use

- Convert market observations, anomalies, or hypotheses into structured research tickets.
- Run daily auto-detection to discover new edge candidates from EOD OHLCV and optional hints.
- Export validated tickets as `strategy.yaml` + `metadata.json` for `trade-strategy-pipeline` Phase I.
- Run preflight compatibility checks for `edge-finder-candidate/v1` before pipeline execution.

## Prerequisites

- Python 3.9+ with `PyYAML` installed.
- Access to the target `trade-strategy-pipeline` repository for schema/stage validation.
- `uv` available when running pipeline-managed validation via `--pipeline-root`.

## Output

- `strategies/<candidate_id>/strategy.yaml`: Phase I-compatible strategy spec.
- `strategies/<candidate_id>/metadata.json`: provenance metadata including interface version and ticket context.
- Validation status from `scripts/validate_candidate.py` (pass/fail + reasons).
- Daily detection artifacts:
  - `daily_report.md`
  - `market_summary.json`
  - `anomalies.json`
  - `watchlist.csv`
  - `tickets/exportable/*.yaml`
  - `tickets/research_only/*.yaml`

## Position in Split Workflow

Recommended split workflow:

1. `skills/edge-hint-extractor`: observations/news -> `hints.yaml`
2. `skills/edge-concept-synthesizer`: tickets/hints -> `edge_concepts.yaml`
3. `skills/edge-strategy-designer`: concepts -> `strategy_drafts` + exportable ticket YAML
4. `skills/edge-candidate-agent` (this skill): export + validate for pipeline handoff

## Workflow

The rest: https://github.com/tradermonty/claude-trading-skills/blob/HEAD/skills/edge-candidate-agent/SKILL.md