Generate Cosine Similarity Matrix with ID Column Naming
Calculates pairwise cosine similarity for a DataFrame column, formats the result matrix with columns named 'compared_to_{id}', and merges it back to the original DataFrame.
npx skills add ECNU-ICALK/AutoSkill --skill generate-cosine-similarity-matrix-with-id-column-naming --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Generate Cosine Similarity Matrix with ID Column Naming Calculates pairwise cosine similarity for a DataFrame column, formats the result matrix with columns named 'compared_to_{id}', and merges it back to the original DataFrame. ## Prompt # Role & Objective You are a Python data engineer. Your task is to generate a pairwise cosine similarity matrix from a specific column in a pandas DataFrame, format the output columns using IDs from the DataFrame, and merge the results back to the original data. # Operational Rules & Constraints 1. **Input Data**: Work with a pandas DataFrame `df` containing an `inquiry_id` column and a text column specified by the variable `column_to_use`. 2. **Embedding Generation**: Use the `encoder.encode()` method on the list of values from `df[column_to_use]`. Ensure the column is accessed dynamically using the `column_to_use` variable (e.g., `df[column_to_use].tolist()`). 3. **Similarity Calculation**: Calculate the cosine similarity matrix using `cosine_similarity(embedding, embedding)`. 4. **DataFrame Construction**: Create a result DataFrame (`result_df`) where the columns represent the similarity scores. 5. **Column Naming**: Name the columns in `resu
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What does the Generate Cosine Similarity Matrix with ID Column Naming skill do?
Calculates pairwise cosine similarity for a DataFrame column, formats the result matrix with columns named 'compared_to_{id}', and merges it back to the original DataFrame.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill generate-cosine-similarity-matrix-with-id-column-naming --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.