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$12.00designUniversal

hf-summarize

Fast, reliable text summarization using the specialized BART-large-CNN model via Hugging Face.

skill install https://www.promptspace.in/skills/hf-summarize

What it does

This skill provides a high-performance summarization interface for your AI agent. It offloads heavy NLP processing to Hugging Face's dedicated BART-large-CNN model, allowing your agent to condense long technical documents or articles into concise summaries without consuming its own context window unnecessarily.

Why use this skill

Standard LLM prompts for summarization can be expensive and prone to "hallucinating" details from their own training data. This skill utilizes a specialized sequence-to-sequence model designed specifically for abstractive summarization. It offers granular control over output length via flags and automatically archives every summary into a local JSON store for historical reference and auditability.

Supported tools

  • Python Requests: Communicates with the Hugging Face Inference API.
  • Local Storage: Automatically manages summary logs in a dedicated hidden directory.
  • File System: Directly reads local text files for bulk processing.

The output includes the generated summary, a comparison of original vs. summary length, and the specific parameters used for the generation.

Use cases

  • Condense lengthy technical documentation into executive summaries
  • Archive summarized research for easy retrieval and local logging
  • Reduce context window usage by pre-summarizing large text files
  • Automate high-quality summary generation for news or articles

Example

Prompt

Summarize the long research paper in research.txt with a max length of 100 words.

Sample output preview is available after purchase.

Frequently asked questions

This skill summarizes long documents using a specialized BART model, which reduces token usage in your main LLM's context window and minimizes the hallucination risks often found in general-purpose models.
hf-summarize — AI Agent Skill | PromptSpace