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Natural Language Processing

Checked
aj-geddes·vlatest·ai-ml·MIT

This NLP skill converts human text into data and insights, enabling machines to understand and respond like people – incredibly useful for automation & analysis.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it Natural Language Processing, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add aj-geddes/useful-ai-prompts --skill "Natural Language Processing" -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

aj-geddes

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3f5182cfd7
Manifest
skills/natural-language-processing/SKILL.md
Scanned
3 files, 382 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The Natural Language Processing skill enables AI agents to understand, interpret, and generate human language with high accuracy. It facilitates tasks like sentiment analysis, text summarization, and entity extraction directly within your agent's workflow.

When to use it

  • Analyze customer feedback to automatically detect positive or negative sentiments in reviews.
  • Summarize long technical documentation into concise bullet points for quick team reference.
  • Extract specific entities like dates, names, or locations from unstructured meeting notes.
  • Classify incoming support tickets into predefined categories based on their content.

Key capabilities

  • Sentiment analysis to gauge emotional tone in text.
  • Text summarization to condense large volumes of information.
  • Named entity recognition for identifying key data points.
  • Language classification to detect the source language of input.

Example prompts

  • "Analyze the sentiment of these five customer reviews and provide a score from 1 to 5."
  • "Summarize the following article about climate change into three main points."
  • "Extract all phone numbers and email addresses from this block of text."

Tips & gotchas

Ensure input text is clean and free of excessive formatting errors, as these can skew analysis results. While powerful for structured tasks, complex reasoning may still require additional logic beyond basic NLP functions.