What is edge-candidate-agent?

A research-ticket generator for long-only United States stock strategies. It turns end-of-day market observations and hypotheses into validated specifications for another trading pipeline.

Finding possible trading edges, prioritizing research tickets, exporting strategy files, and running compatibility checks before pipeline execution.

It turns informal market ideas into reproducible, structured candidates and checks whether they match the pipeline’s required format.

edge-candidate-agent — Skill for Claude Code and Codex by mphinance

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 mphinance/alpha-skills --skill edge-candidate-agent

Clone the repo

git clone --depth 1 https://github.com/mphinance/alpha-skills

Made for: Claude Code, Codex.

Or install quant-skills, the plugin that ships this one along with the rest of its 20 skills.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/mphinance/alpha-skills/edge-candidate-agent/github.svg)](https://agentmods.dev/skills/mphinance/alpha-skills/edge-candidate-agent)

Your own site

<a href="https://agentmods.dev/skills/mphinance/alpha-skills/edge-candidate-agent"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/edge-candidate-agent/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/mphinance/alpha-skills/edge-candidate-agent"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/edge-candidate-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,314 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.

Model	Per session	Once invoked
Fable 5.1	$0.00085	$0.01314
Opus 5	$0.00043	$0.00657
Sonnet 5	$0.00017	$0.00263
Haiku 4.5	$0.00009	$0.00131

Measured 9d ago against content hash 6c9545ce9662, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

edge-candidate-agent 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 9d ago.

The scan reads SKILL.md. This mod also ships 9 executable files (scripts/auto_detect_candidates.py, scripts/candidate_contract.py, scripts/export_candidate.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-candidate-agent — 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.

plugins/quant-skills/skills/edge-candidate-agent/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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:

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

Workflow

Run auto-detection from EOD OHLCV:
- skills/edge-candidate-agent/scripts/auto_detect_candidates.py
- Optional: --hints for human ideation input
- Optional: --llm-ideas-cmd for external LLM ideation loop
Load the contract and mapping references:
- references/pipeline_if_v1.md
- references/signal_mapping.md
- references/research_ticket_schema.md
- references/ideation_loop.md
Build or update a research ticket using references/research_ticket_schema.md.
Export candidate artifacts with skills/edge-candidate-agent/scripts/export_candidate.py.
Validate interface and Phase I constraints with skills/edge-candidate-agent/scripts/validate_candidate.py.
Hand off candidate directory to trade-strategy-pipeline and run dry-run first.

Read the full file on GitHub · 141 lines

Files

What ships with it

15 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.

9d ago First seen · 141 lines · 85 tokens per session scan A 6c9545ce9662

Subscribe to this mod's changes

edge-candidate-agent is a skill published in the GitHub repository mphinance/alpha-skills (21 stars, last pushed 11d ago), licensed MIT. It adds 85 tokens to every session and 1,314 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to edge-candidate-agent, differing in 0 lines, and is treated as a copy.

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