word-letter-frequency

# Word Letter Frequency ## Quick start 1. Identify the input text (typically one word or a short phrase). Default behavior lowercases the text and ignores non-letters so repeated letters like `a`/`A` are merged. 2. Run `scripts/count_letters.py "<text>"` to get a frequency table. Use the optional flags when needed: - `--case-sensitive` keeps uppercase and lowercase separate. - `--include-non-alpha` counts digits/punctuation as-is. - `--json` returns machine-friendly JSON for downstream processing. 3. Summarize the counts for the user. Include clarifying notes (e.g., whether you ignored punctuation) when relevant. ## Script reference ### scripts/count_letters.py Lightweight CLI/utility that powers this skill. It exposes two layers: - **CLI usage**: `python3 scripts/count_letters.py "balloon" --json` - **Import usage**: `from scripts.count_letters import count_letters` and call `count_letters(text, case_sensitive=False, include_non_alpha=False)` to get a `collections.Counter`. Sample CLI output (default options): ``` $ python3 scripts/count_letters.py "balloon" Character Count --------- ----- a 1 b 1 l 2 o 2 n 1 ``` Sample JSON output (good for embedding directly into responses): ``` $ python3 scripts/count_letters.py "AaB!" --case-sensitive --include-non-alpha --json {"A": 1, "a": 1, "B": 1, "!": 1} ``` ## Response patterns - **Concise summary**: “`balloon` contains `b×1, a×1, l×2, o×2, n×1` (case-insensitive, punctuation ignored).” - **Tabular snippet**: Mirror the script’s table for readability. Mention any options you used. - **JSON / dict**: When the user wants structured data, reuse the script’s `--json` flag. ## Edge cases & tips - Make sure to state how you treated uppercase letters and punctuation, especially when the counts differ depending on options. - If the input contains no alphabetic characters and `--include-non-alpha` is not set, the script intentionally reports “(no characters were counted)”. Explain why in the response. - For multiple words, either run the script once on the full phrase (default) or note that the skill focuses on short strings; if the request expands to full documents, escalate to a general text-analysis workflow instead.