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Agent skill

Edge Hint Extractor

by tradermonty in tradermonty/claude-trading-skills

Extract edge hints from daily market observations and news reactions, with optional LLM ideation, and output canonical hints.yaml for downstream concept synthesis and auto detection.

MITAuto-check passedAgent Workflows

Install Edge Hint Extractor

skills CLI
$ npx skills add tradermonty/claude-trading-skills --skill edge-hint-extractor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install tradermonty/claude-trading-skills edge-hint-extractor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/edge-hint-extractor .claude/skills/edge-hint-extractor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
edge-hint-extractor
GitHub stars
3k
Used in
1 other repo
Token cost
~663 tokens
SKILL.md length
187 words
Files
7 (incl. scripts, references)
Skills in repo
74
Repo updated
First seen
Licence
MIT

At a glance

Extract edge hints from daily market observations and news reactions, with optional LLM ideation, and output canonical hints.yaml for downstream concept synthesis and auto detection.

  • Works in 4 steps: Gather observation files… → Run scripts/build_hints.py to generate… → Optionally augment hints with LLM ideas… → …
  • Tasks that involve Brainstorming
  • SKILL.md covers Overview, When to Use, Prerequisites and Output, plus 3 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Edge Hint Extractor is an agent skill from tradermonty/claude-trading-skills. Extract edge hints from daily market observations and news reactions, with optional LLM ideation, and output canonical hints.yaml for downstream concept synthesis and auto detection.

Its SKILL.md is about 660 tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/hints_schema.md` and `scripts/build_hints.py`).

It sits in Agent Workflows, covering Brainstorming. The repository describes itself as: Claude Code skills for equity investors and traders — market analysis, technical charting, economic calendars, screeners, and trading strategy development. The licence is MIT.

When your agent uses it

  • Tasks that involve Brainstorming

Example prompts

  • “/edge-hint-extractor”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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
  4. Pass hints.yaml into concept synthesis or auto detection.

What it can do on your machine

Read from SKILL.md and the folder at commit eab8d5c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Edge Hint Extractor loads about 663 tokens when it runs, and up to ~1.1k if it reads all its reference files. Until then it costs about 51 tokens; SKILL.md has 187 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~663
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from tradermonty/claude-trading-skills at commit eab8d5c, republished under its MIT licence (© tradermonty). 187 words, ~663 tokens.

Download SKILL.mdSave it as .claude/skills/edge-hint-extractor/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
edge-hint-extractor
description
Extract edge hints from daily market observations and news reactions, with optional LLM ideation, and output canonical hints.yaml for downstream concept synthesis and auto detection.

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):

bash
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):

bash
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/

Rule + LLM augmentation (pre-written file, for Claude Code):

bash
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-file /tmp/llm_hints.yaml \
  --output-dir reports/

Resources

  • skills/edge-hint-extractor/scripts/build_hints.py
  • references/hints_schema.md

© tradermonty, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in skills/edge-hint-extractor of tradermonty/claude-trading-skills.

  • SKILL.md
  • agents/openai.yaml
  • references/hints_schema.md
  • requirements.txt
  • scripts/build_hints.py
  • scripts/tests/conftest.py
  • scripts/tests/test_build_hints.py

Open the folder on GitHubat commit eab8d5c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in tradermonty/claude-trading-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Categories

Questions about Edge Hint Extractor

What does Edge Hint Extractor do?

Extract edge hints from daily market observations and news reactions, with optional LLM ideation, and output canonical hints.yaml for downstream concept synthesis and auto detection. Edge Hint Extractor is an agent skill from tradermonty/claude-trading-skills.yaml for downstream concept synthesis and auto detection.

When should I use Edge Hint Extractor?

Edge Hint Extractor fits situations like: tasks that involve Brainstorming.

How do I install Edge Hint Extractor in Claude Code?

Run `npx skills add tradermonty/claude-trading-skills --skill edge-hint-extractor -a claude-code`. Or copy the skill folder (skills/edge-hint-extractor in tradermonty/claude-trading-skills) into .claude/skills/edge-hint-extractor in your project. Claude Code loads it when a task matches its description.

How do I install Edge Hint Extractor in Codex?

Run `npx skills add tradermonty/claude-trading-skills --skill edge-hint-extractor -a codex`. Or copy the skill folder (skills/edge-hint-extractor in tradermonty/claude-trading-skills) into .agents/skills/edge-hint-extractor in your project. Codex loads it when a task matches its description.

Can I use Edge Hint Extractor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tradermonty/claude-trading-skills --skill edge-hint-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/edge-hint-extractor, .gemini/skills/edge-hint-extractor, .github/skills/edge-hint-extractor and .opencode/skills/edge-hint-extractor in your project.

What does Edge Hint Extractor need to run?

Going by SKILL.md and its folder, Edge Hint Extractor needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Edge Hint Extractor access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Edge Hint Extractor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Edge Hint Extractor use?

Edge Hint Extractor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Edge Hint Extractor use?

About 663 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 430 tokens, read only when the agent opens those files.

What are the alternatives to Edge Hint Extractor?

Skills that share tags, products or a category with Edge Hint Extractor: Brainstorming (obra/superpowers, 297k stars), Brainstorming (xpinjection/test-driven-spring-boot, 112 stars), Yao Meta Skill (yaojingang/yao-meta-skill, 2.7k stars) and Typesafe AI (OpenAgentsInc/openagents, 455 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Edge Hint Extractor?

tradermonty (a GitHub user) maintains it in tradermonty/claude-trading-skills, which has 2,977 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on October 9, 2026.

Source: tradermonty/claude-trading-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.