Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →nicepkg/canslim-screener
Screen US stocks using William O'Neil's CANSLIM growth stock methodology.
Passed 14 of 19 test cases with the skill, and 3 of 19 without it.
and 13 more in the full report
13 fixed3 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write the command line invocation for `screen_canslim.py` to evaluate custom tickers AAPL, MSFT, and NVDA using an API key stored in the environment variable `FMP_API_KEY`.
| Checked | Without skill | With skill |
|---|---|---|
| Uses the `--universe` option to pass stock ticker symbols to the Python script. | Missed | Passed |
| Specifies `--api-key $FMP_API_KEY` in the command execution. | Passed | Passed |
The instructions your model reads when the skill loads.
This skill screens US stocks using William O'Neil's proven CANSLIM methodology, a systematic approach for identifying growth stocks with strong fundamentals and price momentum. CANSLIM analyzes 7 key components: Current Earnings, Annual Growth, Newness/New Highs, Supply/Demand, Leadership/RS Rank, Institutional Sponsorship, and Market Direction.
Phase 2 implements 6 of 7 components (C, A, N, S, I, M), representing 80% of the full methodology. This phase adds critical volume analysis (S) and institutional ownership tracking (I) to the Phase 1 foundation.
Two-Stage Approach:
Key Features:
Phase 2 Component Weights (Renormalized for 6 components):
Future Phases:
Explicit Triggers:
test cases passed, vs 3 / 19 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.