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Standardizes and cleans raw text data to improve AI processing accuracy and output quality.
This skill provides a standardized methodology for cleaning noisy text data. It removes irrelevant characters, fixes formatting issues, and prepares text for downstream AI analysis or generation.
Use this skill when dealing with raw scrapes, OCR output, or messy logs that need to be normalized before being used as context for a LLM.
Any agent adhering to the Agent Skills open standard, including Claude Code, Cursor, and other MCP-enabled environments.
This skill has not been reviewed by our automated audit pipeline yet.
arxiv2md
Convert arXiv papers into clean, LLM-ready Markdown via a REST API or CLI for fast reading, summarization, and downstream processing.
Generate Multilingual Sentences with Contextual Definitions
Produce multiple example sentences using a target word in varied meanings, translate them into a target language, and show the contextual meaning of the word fo
Humanize AI Text
Rewrite AI-generated text into more natural, human-like prose using the HumanizerAI API, with before/after scores and credit tracking.
DSPy — Declarative LM Programming
Use DSPy to build declarative, modular LM pipelines, optimize prompts automatically, and assemble reliable RAG/agent systems with structured signatures and opti
Webshop Query Parser
Parse shopping instructions into structured search criteria (product, attributes, price limits) to guide product discovery and filtering.
LLM Evaluation
Evaluation framework and tools for systematically measuring LLM performance using automated metrics, human judgment, and A/B testing.
Write-Skill: AI Writing Cleanup
Edit and rewrite text to remove AI-generated patterns and make prose sound more natural and human.
Wit.ai Integration (Membrane)
Integrates Wit.ai via the Membrane CLI to list and manage apps, intents, entities, traits and utterances; can proxy API requests while handling authentication a