edge-hint-extractor

edge-hint-extractor is a skill for Codex from BaggaT236/AI-Trading-Skills. It costs 37 tokens per session (682 once invoked), scanned A, a copy of edge-hint-extractor, MIT.

A tool that turns daily market observations, unusual events, and reactions to news into structured trading ideas. It can save these ideas in a hints.yaml file for later research.

In plain words
What is it for?
Use it to create rule-based hints, optionally add ideas from a language model, and prepare hints for concept synthesis or automatic detection.
Why use it?
It removes the manual work of turning scattered market data into a consistent input for strategy development.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Claude Code.

Good fit Use it to create rule-based hints, optionally add ideas from a language model, and prepare hints for concept synthesis or automatic detection.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/edge-hint-extractor/github.svg)](https://agentmods.dev/skills/baggat236/ai-trading-skills/edge-hint-extractor)
Your own site
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/edge-hint-extractor"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/edge-hint-extractor/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-hint-extractor

Your own site · 80×15
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/edge-hint-extractor"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/edge-hint-extractor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 682 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 $0.00037 $0.00682
Opus 5 $0.00018 $0.00341
Sonnet 5 $0.00007 $0.00136
Haiku 4.5 $0.00004 $0.00068

Measured 12d ago against content hash 875efa932dbd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

edge-hint-extractor 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/build_hints.py, scripts/tests/conftest.py, scripts/tests/test_build_hints.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-hint-extractor — 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-hint-extractor/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Edge Hint Extractor

Overview

Convert raw observation signals (market_summary, anomalies, news reactions) into structured edge hints. This skill is the first stage in the split workflow: observe -> abstract -> design -> pipeline.

When to Use

  • You want to turn daily market observations into reusable hint objects.
  • You want LLM-generated ideas constrained by current anomalies/news context.
  • You need a clean hints.yaml input for concept synthesis or auto detection.

Prerequisites

  • Python 3.9+
  • PyYAML
  • Optional inputs from detector run:
    • market_summary.json
    • anomalies.json
    • news_reactions.csv or news_reactions.json

Output

  • hints.yaml containing:
    • hints list
    • generation metadata
    • rule/LLM hint counts

Workflow

  1. Gather observation files (market_summary, anomalies, optional news reactions).
  2. Run scripts/build_hints.py to generate deterministic hints.
  3. Optionally augment hints with LLM ideas via one of two methods:
    • a. --llm-ideas-cmd — pipe data to an external LLM CLI (subprocess).
    • b. --llm-ideas-file PATH — load pre-written hints from a YAML file (for Claude Code workflows where Claude generates hints itself).
  4. Pass hints.yaml into concept synthesis or auto detection.

Note: --llm-ideas-cmd and --llm-ideas-file are mutually exclusive.

Quick Commands

Rule-based only (default output to reports/edge_hint_extractor/hints.yaml):

python3 skills/edge-hint-extractor/scripts/build_hints.py \
  --market-summary /tmp/edge-auto/market_summary.json \
  --anomalies /tmp/edge-auto/anomalies.json \
  --news-reactions /tmp/news_reactions.csv \
  --as-of 2026-02-20 \
  --output-dir reports/

Rule + LLM augmentation (external CLI):

python3 skills/edge-hint-extractor/scripts/build_hints.py \
  --market-summary /tmp/edge-auto/market_summary.json \
  --anomalies /tmp/edge-auto/anomalies.json \
  --llm-ideas-cmd "python3 /path/to/llm_ideas_cli.py" \
  --output-dir reports/

Read the full file on GitHub · 83 lines

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 · 83 lines · 37 tokens per session scan A 875efa932dbd

Subscribe to this mod's changes

edge-hint-extractor is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 8d ago), licensed MIT. It adds 37 tokens to every session and 682 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-hint-extractor, differing in 0 lines, and is treated as a copy.

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