# CANSLIM-Top100-US

> Analyze the top 100 S&P 500 companies by market capitalization using CANSLIM-style signals and return a ranked shortlist in Markdown.

- Skill: `dvcrn/canslim-top100-us` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add dvcrn/canslim-top100-us`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dvcrn/canslim-top100-us/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Docs & Writing
- Author: dvcrn (https://skillmd.com/u/dvcrn)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/dvcrn/canslim-top100-us

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# CANSLIM S&P 500 Analyzer

Analyze the top 100 S&P 500 stocks by market capitalization using the local `analyzer.py` script, then summarize the strongest candidates for the user.

## When to use
Use this skill when the user asks to:
- Run a CANSLIM analysis on large-cap U.S. stocks.
- Screen S&P 500 leaders by growth, momentum, and institutional-quality signals.
- Generate a ranked shortlist of CANSLIM-style candidates.

## Inputs
Expected local files:
- `Scripts/analyzer.py`
- `Scripts/requirements.txt` (if dependencies are not already installed)

Expected script output:
- `canslim_results.json` (in root directory)
- Optional: `canslim_results.csv`

## Execution rules
Follow this checklist exactly:
1. Confirm that `Scripts/analyzer.py` exists.
2. If dependencies are missing, install them from `Scripts/requirements.txt`.
3. Change to the Scripts directory or run `python Scripts/analyzer.py` from root.
4. Wait for the script to finish successfully.
5. Read `canslim_results.json`.
6. Rank stocks by CANSLIM score from highest to lowest.
7. Present the best candidates in a Markdown table.
8. Explain which CANSLIM letters each top stock passed or failed.
9. If no stock is a strong match, show the top 3 closest candidates instead.

## Analysis guidance
Interpret the script output using these principles:
- `C`: strong recent quarterly earnings growth.
- `A`: strong annual growth trend.
- `N`: price near new highs or supported by a fresh catalyst.
- `S`: favorable supply-demand signal such as strong volume.
- `L`: market leadership versus weaker peers.
- `I`: meaningful institutional sponsorship.
- `M`: favorable trend or market direction signal.

Do not invent missing metrics. If any field is unavailable, say that the data is unavailable and continue with the remaining signals.

## Output format
Return:
- A 1-2 sentence overall assessment.
- A Markdown table with the top candidates.
- A short bullet list explaining why the top names ranked highly.
- A note listing any missing data, weak signals, or caveats.

Use this table format:

| Rank | Ticker | Company | Score | Passed | Failed | Notes |
|---|---|---|---:|---|---|---|

## Constraints
- Use only the files generated by this skill run.
- Do not claim the results are investment advice.
- Do not fabricate company names, prices, or scores.
- If the script fails, clearly report the failure and suggest checking dependencies or network access for market data.

## Failure handling
If execution fails:
- State which step failed.
- Include the error message if available.
- Recommend the smallest next action, such as installing dependencies or rerunning the script.