trader-screener

1# trader-screener
2 
3A screen turns "I want profitable companies that are still growing and not
4too expensive" into rules a computer can check, and shows its work: every
5pass and every fail comes with the number and the threshold.
6 
7Tool in this folder (standard library Python, no network):
8 
9```bash
10python3 "${CLAUDE_SKILL_DIR}/screen.py" --help
11```
12 
13## What it reads and writes
14 
15- Metrics: `trader/metrics.json` from `/trader-analyst` (`facts.py --metrics`),
16  or any JSON list or CSV with a `ticker` column. CSV numbers may carry `$`,
17  `%` and commas.
18- Prices (optional): `trader/prices.json` (`{"prices": {"AAPL": 341.27}}`,
19  any source; `/trader-alerts` writes it). With prices it adds `price`, `pe`
20  (price / trailing EPS, only when EPS is positive) and `earnings_yield`.
21- Rules: a JSON file, `rules.example.json` in this folder to start from.
22- Writes `trader/shortlist.json` with `--out`: who passed, their score and
23  why, who failed and why.
24 
25## The rules file
26 
27```json
28{"name": "Growing, profitable, not priced for perfection",
29 "rules": [{"metric": "revenue_growth_yoy", "op": ">=", "value": 10},
30           {"metric": "operating_margin", "op": ">=", "value": 25},
31           {"metric": "pe", "op": "<=", "value": 35}],
32 "rank":  [{"metric": "revenue_growth_yoy", "order": "desc", "weight": 2},
33           {"metric": "pe", "order": "asc", "weight": 1}],
34 "missing": "fail"}
35```
36 
37Ops: `>`, `>=`, `<`, `<=`, `==`, `!=`, `between` ([low, high]), `in` and
38…