Traction scoreGitHub stars can be faked, so popularity alone can be misleading. Traction Score looks for broader signs of recent attention, adoption, and active maintenance.
This skill tracks individual tickers to notify users when specific price targets, stop rules, or percentage moves from the previous close are met. It integrates NYSE market hours and holiday schedules to manage alerts for opening bells and early closes.
By fetching delayed quotes and maintaining a local price registry, it provides the necessary data for traders to monitor their positions without manual refreshing.
Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.
Set sec_user_agent in trader/config.json, or set the SEC_USER_AGENT environment variable. Replace the example identity "Your Name you@example.com" with your real name and email.
Installs: Copy the complete set of trader-* skill folders into ~/.claude/skills/ for global availability with plain names such as /trader-copycat. · Claude Code
Before you start
Claude Code.
Git for the documented clone command.
Python 3.8 or newer for the tools; no pip installation is needed.
Configure your real name and email as the SEC User-Agent before using SEC-dependent tools.
Run this complete block in a terminal to clone the repository and copy its trader-* folders into the global Claude skills directory.
Set sec_user_agent in trader/config.json, or set the SEC_USER_AGENT environment variable. Replace the example identity "Your Name you@example.com" with your real name and email.
Your real name and email configured through sec_user_agent in trader/config.json or SEC_USER_AGENT.
Use trader-analyst to summarize AAPL's latest reported quarter. Give revenue, diluted EPS, year-over-year growth, and margins, with links to the filings. Flag unusual items, derived figures, or stale SEC facts, and read the latest earnings release or 10-Q when needed for context.
A supplied CSV with a ticker column and revenue_growth_yoy and operating_margin metrics; include company data dates when available.
Python 3.8 or newer. The screener itself needs no network access.
Use trader-screener on the metrics CSV I provide. Require revenue_growth_yoy of at least 10 and operating_margin of at least 25, failing companies with missing required metrics. Rank passing companies by revenue_growth_yoy descending. Show each pass and fail with its actual value and threshold, and report the dates of the numbers when available.
Configure your real name and email through sec_user_agent in trader/config.json or SEC_USER_AGENT to include SEC filings; without it, only headlines run.
Use trader-news to check AAPL news and 8-K filings from the past 24 hours. Read the important source stories or filings before summarizing them, and give a short brief with source links. Flag earnings, legal, and risk items; identify anything you cannot read. If nothing is new, say so.
Claude