Clearstreet screener

Skill clear-street/clearstreet-skills/skills/clearstreet-screener

Run a fundamentals-and-analyst-aware stock screener across ~11,000 US instruments. Filter by sector, industry, country, market-cap range, P/E (TTM), debt/equity, dividend yield, consensus rating (BUY/HOLD/SELL), and price-target upside. Use when the user asks "find me stocks where…", "screen for…", or "what names look cheap/undervalued". For a single-ticker drill-down, chain to clearstreet-fundamentals-deep-dive.From its SKILL.md

Install

npx -y skills add clear-street/clearstreet-skills --skill clearstreet-screener

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One thing to look at

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SKILL.md

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Screener

Filter the full Clear Street instrument universe by fundamentals and analyst metrics, then return a ranked markdown table.

Prerequisites

Python 3.9+ (standard library only)
CLEARSTREET_API_KEY set in the environment — see the repo README

Quick start

# Large-cap US tech with consensus BUY and P/E under 30, sorted by upside
python3 scripts/screen.py \
  --sector Technology --country US \
  --market-cap-min 50000000000 --pe-max 30 \
  --rating BUY --sort upside_pct --top 20

Examples

Ask	Command
"US tech, BUY rating, P/E under 25"	`screen.py --sector Technology --country US --rating BUY --pe-max 25`
"Large-cap dividend payers, yield > 3%"	`screen.py --market-cap-min 10000000000 --div-yield-min 0.03 --sort div_yield`
"Healthcare names with biggest upside"	`screen.py --sector Healthcare --rating BUY --sort upside_pct --top 15`
"Small-caps under $2B, P/E under 10"	`screen.py --market-cap-max 2000000000 --pe-max 10 --pe-min 0`
"ETFs only"	`screen.py --instrument-type ETF`

Common flags

Flag	Notes
`--sector`, `--industry`, `--country`, `--exchange`	Categorical filters
`--instrument-type`	`COMMON_STOCK`, `EXCHANGE_TRADED_FUND`, `MUTUAL_FUND` (aliases accepted: `stock`, `etf`, `fund`)
`--market-cap-min` / `-max`	Dollars (10B = `10000000000`)
`--pe-min` / `-max`	Trailing P/E (TTM)
`--div-yield-min` / `-max`	Fraction (`0.02` = 2%)
`--rating`	`BUY`, `HOLD`, `SELL`, `STRONG_BUY`, `STRONG_SELL`
`--upside-pct-min` / `-max`	(target − price) / price × 100
`--sort FIELD [asc\|desc]`	`market_cap`, `upside_pct`, `pe`, `div_yield`, `price`, `total_ratings`, `name`, `symbol`
`--top`	Max rows (default 25)
`--cache PATH`	Cache the universe locally for faster repeated screens

Full flag list: see reference.md.

Workflow

Translate the user's natural-language criteria into flags.
Run screen.py. For repeated screens in one session, pass --cache /tmp/cs_universe.json.
Present the ranked markdown table.
To drill into a result, chain to clearstreet-fundamentals-deep-dive <symbol>.

Safety

Read-only. The full fetch is ~58 sequential GET requests with built-in backoff for rate limits. Output is informational, not investment advice.

What ships with it: 3 files

14.7 KB alongside SKILL.md, 2 of them executable

scripts/

clearstreet_client.pyruns3.8 KB
screen.pyruns8.9 KB

reference.md2.0 KB