Sentiment Analyzer
CheckedThis Sentiment Analyzer identifies the emotional tone (positive, negative, neutral) of text, helping you understand customer feedback or social media reactions.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
Sentiment Analyzer, not the name it is listed under, so the command below uses that name.- 1
Run this in your project
terminal$ npx skills add jmsktm/claude-settings --skill "Sentiment Analyzer" -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
jmsktm
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.
Automated safety checks
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 jmsktm/claude-settings at c113b0d7e1.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- c113b0d7e1
- Scanned
- 1 file, 299 lines
About this skill
What it does
This skill analyzes text and determines its sentiment, classifying it as positive, negative, or neutral. It provides a score indicating the strength of the sentiment detected. The tool is useful for understanding customer feedback, gauging public opinion on social media, or assessing the tone of written communication.
When to use it
- Analyze customer reviews to identify areas for product improvement.
- Monitor social media mentions to understand brand perception.
- Assess the emotional tone of internal communications (e.g., emails, meeting transcripts).
- Evaluate survey responses to gauge participant satisfaction.
Key capabilities
- Sentiment classification (positive, negative, neutral)
- Sentiment scoring (strength of sentiment)
- Text analysis
Example prompts
- "Analyze the sentiment of this customer review: 'The product was amazing and exceeded my expectations!'"
- "What is the sentiment score for this tweet: 'I'm so frustrated with the slow service.'"
- "Determine the overall sentiment of this email thread."
Tips & gotchas
The accuracy of the analysis depends on the clarity and context of the input text. Sarcasm or nuanced language may be misinterpreted, leading to inaccurate results.