trader-screener

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

1. Turn the user's words into rules. Ask when a threshold is vague ("cheap" means what P/E?). Write them to trader/rules.json.

2. Get metrics for the candidates: run /trader-analyst on them with --metrics trader/metrics.json (its facts.py AAPL AXP GOOGL KO BAC --metrics trader/metrics.json), or use the user's own CSV. Prices from trader/prices.json if P/E matters.

3. Run the screen:

   python3 "${CLAUDE_SKILL_DIR}/screen.py" trader/metrics.json --rules trader/rules.json \
     --prices trader/prices.json --out trader/shortlist.json
   

   Exit code 1 means nothing passed: say so and show the closest misses.

4. Report the shortlist with the reasons, the misses with the numbers that failed, and the dates the numbers are from (the latest quarter end per company, the price date). Suggest /trader-analyst on the top names before anything else.

Example: the reel's five

Metrics from SEC for AAPL, AXP, GOOGL, KO and BAC, prices at the 2026-10-13 close, and rules.example.json:

Growing, profitable, not priced for perfection: 2 of 5 companies pass.
 1. PASS GOOGL  Alphabet Inc.  score 0.75   (growth 24.2, P/E 17.8)
 2. PASS KO     COCA COLA CO   score 0.25   (growth 12.1, P/E 28.3)
    FAIL AAPL   pe 39.2, needs <= 35
    FAIL BAC    operating_margin is missing
    FAIL AXP    revenue_growth_yoy 8.6, needs >= 10; operating_margin is missing

Then the caveats a careful analyst adds: Alphabet's latest quarter has net income above operating income (gains outside the business), and Coca-Cola's numbers stop at the quarter ending 2026-04-03 because SEC's facts lag its latest 10-Q.

What it never does

• Never calls a passing company a buy. A screen is a filter on reported numbers, not a recommendation.
• Never fills in a missing number or guesses a metric: missing means missing.
• Never sends anything to /trader-budget or an order path by itself.

Safety

Education and tooling, not financial advice. This skill only filters numbers. Nothing places an order except /trader-broker, after /trader-risk passes and the user types an explicit yes for that order.