hf-sentiment
by Kevin Cline
Automated sentiment analysis and batch text classification using Hugging Face's Inference API.
- Classify customer feedback sentiment in bulk from local log files.
- Automate sentiment scoring for social media mentions or review datasets.
- Generate structured JSON datasets of text sentiment for machine learning.
Secure checkout via Stripe
Included in download
- Classify customer feedback sentiment in bulk from local log files.
- Generate structured JSON datasets of text sentiment for machine learning.
- terminal, network, env_vars automation included
- Includes example output and usage patterns
See it in action
A real example of what this skill takes in and produces.
Sample output
[1] POSITIVE (99.8%) — Build quality is amazing. [2] NEGATIVE (85.4%) — The software update ruined the battery life. [3] POSITIVE (92.1%) — Fast shipping and great support.
Results saved to: ~/.hf-sentiment/sentiment_20231024_120000.json
hf-sentiment
by Kevin Cline
Automated sentiment analysis and batch text classification using Hugging Face's Inference API.
Secure checkout via Stripe
Included in download
- Classify customer feedback sentiment in bulk from local log files.
- Generate structured JSON datasets of text sentiment for machine learning.
- terminal, network, env_vars automation included
- Includes example output and usage patterns
- Instant install
See it in action
A real example of what this skill takes in and produces.
Sample output
[1] POSITIVE (99.8%) — Build quality is amazing. [2] NEGATIVE (85.4%) — The software update ruined the battery life. [3] POSITIVE (92.1%) — Fast shipping and great support.
Results saved to: ~/.hf-sentiment/sentiment_20231024_120000.json
About This Skill
What it does
This skill provides a high-performance sentiment analysis interface powered by Hugging Face's Inference API. It allows your AI agent to classify text as positive or negative with confidence scores, moving beyond simple guess-work to use industry-standard transformer models (DistilBERT).
Why use this skill
While LLMs can estimate sentiment, they are often inconsistent and expensive for high-volume tasks. This skill provides a structured, reproducible way to process data by offloading the heavy lifting to specialized sentiment models. It handles the API overhead, batch processing logic, and local storage of results, making it ideal for developers building data pipelines or monitoring tools.
Supported features
- Single & Batch Processing: Analyze individual strings or process multiple inputs in a single request for efficiency.
- File-Based Workflows: Point the skill to a text file for line-by-line automated analysis.
- Persistent Storage: All results are automatically versioned and saved as JSON in a local directory for later retrieval or auditing.
- Low Latency: Utilizes the DistilBERT-SST-2 model for fast, accurate results without the overhead of a full GPT-4 call.
Use Cases
- Classify customer feedback sentiment in bulk from local log files.
- Automate sentiment scoring for social media mentions or review datasets.
- Generate structured JSON datasets of text sentiment for machine learning.
- Perform fast, model-backed sentiment checks within local dev workflows.
How to Install
mkdir -p ~/.claude/skills && curl -sL https://www.agensi.io/api/install/hf-sentiment | tar xz -C ~/.claude/skills/Free skills install directly. Paid skills require purchase - use the download button above after buying.
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Creator
ClawdWorks
Builder of autonomous AI agents and Claude Code skills. ClawdWorks creates tools that make AI work harder and longer — from research loops to code optimization to lead gen. Powered by Claude Opus 4.6 + Codex 5.4.
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