Skill UI

ADHX provides a dedicated API to fetch X/Twitter posts as clean, structured JSON. It extracts comprehensive data, including author profiles, engagement metrics (likes, retweets), and full article content for long-form posts. This method is vastly superior to traditional scraping techniques, making it ideal for LLM analysis, summarization, and structured data workflows.

SimPy is a powerful, process-based discrete-event simulation framework written in Python. It is designed for modeling complex systems where entities interact with shared resources and time-based events occur, such as manufacturing lines, service queues, network traffic, or logistics networks. Use this skill to analyze resource contention, simulate process optimization, conduct capacity planning, and model dynamic system behaviors.

Execute comprehensive, asynchronous transcription workflows using AssemblyAI. This tool handles file upload, queues jobs, and provides advanced audio intelligence features. Capabilities include speaker diarization, sentiment analysis, named entity recognition (NER), topic categorization (IAB), content safety moderation, and sensitive PII redaction. Ideal for processing meeting recordings, interviews, and large volumes of spoken content.

This internal agent skill processes raw X/Twitter posts into structured bug candidates. It systematically performs parsing, content deduplication, PII redaction, reliability scoring, and classification. Finally, it clusters related reports using deterministic signatures, providing a highly organized output for efficient bug triage and analysis from large-scale social media streams.

Implements a robust data pipeline for handling large documents with the Grammarly API. This utility manages text chunking to comply with API character limits (max 100k), processes text in manageable segments, and aggregates multiple scoring metrics (like correctness, clarity, and tone) into a single, comprehensive report. Ideal for large-scale content analysis and data ingestion.

A comprehensive guide for migrating data to, from, and between Notion workspaces. This skill covers complex data pipelines, including rate-limited bulk imports (CSV/JSON), full database exports with pagination, cross-database syncing, and data transformation patterns for integrating content from sources like Confluence and Google Docs. Essential for building robust Notion ETL workflows.

An all-in-one toolkit for deep web research, encompassing web search, content extraction, data enrichment, and multi-source deep reporting. It specializes in academic and scientific sources, prioritizing peer-reviewed papers, preprints, and scholarly databases. Use this skill for comprehensive investigations, literature reviews, or structured data collection from the web.

A comprehensive guide for deep debugging complex Snowflake issues. This guide covers advanced techniques including detailed query profiling (spill analysis), diagnosing lock contention and transaction conflicts, analyzing metadata operations, and optimizing partition usage. Use it when standard troubleshooting fails to address slow queries or warehouse performance bottlenecks.

This tool performs a rigorous Level 2 semantic epistemic review of Agent-Native Research Artifacts (ARAs). It assesses six critical dimensions—including evidence relevance, falsifiability, and methodological rigor—to determine the content's intellectual soundness. It is used after initial structural validation to provide objective, constructive criticism, scoring the work from Strong Accept to Reject.