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EAS Update Health Insights

eas-update-insights

sickn33/agentic-awesome-skills

This skill allows developers to query the health metrics of published EAS Updates directly from the command line. It provides data on crash rates, install counts, unique users, payload sizes, and the split between embedded and OTA users per channel. Useful for post-publish rollout monitoring and regression detection.

EAS Observe Expo Performance Setup

sickn33/agentic-awesome-skills

Set up and query EAS Observe for Expo apps: root integration (AppMetricsRoot/ObserveRoot), interactive markers, per-route metrics, EAS CLI metric summaries, traces, logs, and startup performance diagnosis.

Firebase Backend Development

sickn33/agentic-awesome-skills

Master Firebase backend services including Authentication, Firestore, Realtime Database, Cloud Functions, Storage, and Hosting. Learn security rules, data modeling for read-heavy workloads, and cost optimization to avoid pitfalls like expensive reads and query limitations.

Food Database Query

food-database-query

sickn33/agentic-awesome-skills

This skill enables querying nutritional information, comparing food items, and performing calculations based on structured food data. It supports database retrieval, portion conversion, and classification filtering for precise nutritional analysis rather than general text suggestions.

Frontend Optimistic Mutations

frontend-optimistic-mutations

sickn33/agentic-awesome-skills

A portable discipline for the write path in React or React Native apps using a query/cache layer. It codifies the optimistic-update lifecycle including canceling in-flight queries, snapshotting affected caches, patching instantly, rolling back verbatim on error, and invalidating on success. Ensures the UI feels instant, remains safe on failure, and maintains cache coherence across detail and list views.

GCP Audit Logs Configuration

sickn33/agentic-awesome-skills

Configure GCP Cloud Audit Logs for compliance and security investigation. Set up log sinks to BigQuery, Cloud Storage, and Pub/Sub for export and real-time streaming. Query audit logs to monitor admin activity, data access, and policy changes.

Gemini Deep Research

gemini-deep-research

sickn33/agentic-awesome-skills

Run autonomous multi-step research with Google's Gemini Deep Research Agent. Start a query, stream or poll progress, and collect a cited report for market analysis, literature reviews, and competitive scans.

Relentless Plan Interviewer

sickn33/agentic-awesome-skills

This skill relentlessly interviews users about their plans or designs to stress-test ideas before building. It walks through design trees, resolves dependencies, and asks questions one at a time to ensure shared understanding. It explores codebases when possible and provides recommended answers for each query.

Hugging Face Dataset Management

hugging-face-datasets

sickn33/agentic-awesome-skills

Create, configure, and manage Hugging Face Hub datasets. Supports SQL querying, transformation, filtering, exporting, and pushing subsets or custom datasets to the Hub.

Hugging Face Papers Lookup

hugging-face-papers

sickn33/agentic-awesome-skills

Look up Hugging Face paper pages as markdown and query the papers API for structured metadata including authors, linked models, datasets, Spaces, GitHub repos, and project pages. Ideal for summarizing or analyzing AI research papers from hf.co or arXiv URLs and IDs.

HuggingFace Best Model Finder

huggingface-best

sickn33/agentic-awesome-skills

This skill helps users find the best AI models for specific tasks by querying Hugging Face benchmark leaderboards. It analyzes hardware constraints like GPU VRAM or CPU memory to filter compatible models. The output includes a comparison table with benchmark scores, parameter sizes, licenses, and device compatibility status. It also suggests whether models can run locally or require API access.

YouTube Transcript to Markdown Vault Ingestion

sickn33/agentic-awesome-skills

This skill extracts full transcripts and rich metadata from a single YouTube video URL. It uses yt-dlp to download subtitles, cleans VTT timing markers, and pulls video details (title, channel, date). The output is a structured, queryable Markdown file, ideal for populating a personal knowledge vault and enabling downstream knowledge graph extraction or content repurposing.

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