trader-screener

A screen turns "I want profitable companies that are still growing and not too expensive" into rules a computer can check, and shows its work: every pass and every fail comes with the number and the threshold.

Tool in this folder (standard library Python, no network):

python3 "${CLAUDE_SKILL_DIR}/screen.py" --help

What it reads and writes

• Metrics: trader/metrics.json from /trader-analyst (facts.py --metrics), or any JSON list or CSV with a ticker column. CSV numbers may carry $, % and commas.
• Prices (optional): trader/prices.json ({"prices": {"AAPL": 341.27}}, any source; /trader-alerts writes it). With prices it adds price, pe (price / trailing EPS, only when EPS is positive) and earnings_yield.
• Rules: a JSON file, rules.example.json in this folder to start from.
• Writes trader/shortlist.json with --out: who passed, their score and why, who failed and why.

The rules file

{"name": "Growing, profitable, not priced for perfection",
 "rules": [{"metric": "revenue_growth_yoy", "op": ">=", "value": 10},
           {"metric": "operating_margin", "op": ">=", "value": 25},
           {"metric": "pe", "op": "<=", "value": 35}],
 "rank":  [{"metric": "revenue_growth_yoy", "order": "desc", "weight": 2},
           {"metric": "pe", "order": "asc", "weight": 1}],
 "missing": "fail"}

Ops: >, >=, <, <=, ==, !=, between ([low, high]), in and not in (a list, for tickers or sectors to leave out). "missing": "fail" fails a company that lacks a metric a rule needs (banks have no operating margin in SEC's facts); "skip" ignores that rule for it and says so. Ranking scores each passing company 0 to 1 per rank metric and takes the weighted average.

Steps