This collection should not trap users in comparison mode or pretend to install the whole collection. Its job is to narrow the shortlist to one skill, then send the next click into installation, validation, and rollout. Installation happens on the skill path.
The Next Click Should Keep Narrowing, Not Reset Back To A Generic Directory
Once the install path is clear, move into the solution, CLI, or editorial surface that best matches this collection. That keeps platform, framework, and operations demand narrowing into a more verifiable high-intent journey.
Reviewed on 2026-04-16 against first-party ownership, documentation quality, install clarity, and production relevance. This is the safest collection to lead with after the site's corpus reset.
We prioritize this page because it lets users verify trust first and then move into one installation path, which is stronger for recovery than sending them into another repo crawl.
Trust Signals
- Entries are maintained by first-party product teams or widely trusted ecosystem builders.
- Documentation and install paths are public, active, and easy to validate before rollout.
- Selection favors practical deployment value over generic GitHub popularity.
Grouping Logic
- Lead with first-party tools and ecosystem anchors users can verify without guesswork.
- Keep the shortlist compact enough to compare quickly, but broad enough to cover install, orchestration, observability, and workflow automation.
- Route discovery into one installation path before expanding into broader workflow collections.
Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, React Query, SWR, error handling, caching, offline support, and Expo Router data loaders (useLoaderData).
Complete guide for building beautiful apps with Expo Router. Covers fundamentals, styling, components, navigation, animations, patterns, and native tabs.
This AI agent skill provides expert guidance on designing consistent, developer-friendly REST APIs, including resource naming, status codes, and pagination.
Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitH...
The django-verification skill automates testing, linting, and security scans for Django projects, ensuring quality and security before release or PR. It benefits developers by saving time and reducing errors.
The foundation-models-on-device skill enables developers to build AI-powered features using Apple Intelligence on-device, generating or summarizing text without cloud dependency. It helps developers create privacy-preserving AI features with custom tool calling and snapshot streaming.
This AI agent skill processes documents using the Nutrient DWS API, benefiting developers by automating tasks such as format conversion, text extraction, and data redaction. It helps with AI coding by streamlining document workflows.
This AI agent skill provides comprehensive Perl security guidelines, helping developers ensure secure coding practices and prevent common vulnerabilities.
The santa-method AI agent skill provides multi-agent adversarial verification, helping developers ensure code accuracy and compliance by utilizing two independent review agents.
The search-first AI agent skill systematizes the research-before-coding workflow, assisting developers in finding existing tools and libraries before implementing custom code. This skill benefits developers by saving time and reducing redundant code.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.
Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
This AI agent skill streamlines C++ testing with GoogleTest and CMake, helping developers write and maintain robust tests. It automates test workflows for efficient code validation.
This AI agent skill provides a thorough Flutter/Dart code review, covering widget best practices, state management patterns, and clean architecture. Developers can improve their code quality and productivity with this skill.
The laravel-patterns skill provides production-grade Laravel architecture patterns for scalable and maintainable applications, benefiting developers with improved workflow and app performance.
Rules-distill is an AI agent skill that extracts cross-cutting principles from skills and distills them into rules, enhancing coding productivity. It benefits developers by automating rules maintenance and providing a deterministic collection of principles.
Use this skill when adding authentication, handling user input, working with secrets, creating API endpoints, or implementing payment/sensitive features. Provides comprehensive security checklist and patterns.
The energy-procurement skill helps senior energy managers optimize energy spend across multiple facilities. It analyzes tariff structures, identifies optimization opportunities, and evaluates demand charge mitigation strategies, leveraging AI coding for improved procurement decisions.
This AI agent skill enables retailers to optimize inventory levels through data-driven demand forecasting and automated replenishment planning, benefiting developers and retailers alike by minimizing stockouts and excess inventory.
The production-scheduling AI agent skill helps senior production schedulers optimize job sequencing, line balancing, and changeover optimization, benefiting production management, planning, quality, and maintenance teams by maximizing throughput and meeting customer delivery commitments.
# Browser QA — Automated Visual Testing & Interaction ## When to Use - After deploying a feature to staging/preview - When you need to verify UI behavior across pages - Before shipping — confirm layouts, forms, interactions actually work - When reviewing PRs that touch frontend code - Accessibili...
This AI agent skill provides universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development, helping developers maintain high-quality codebases. It assists in enforcing naming conventions, formatting, and structural consistency.
exa-search is a neural search skill for AI coding assistants, helping developers find relevant information and code examples efficiently. It benefits developers by providing quick access to web content, company research, and people lookup.
Next.js Turbopack accelerates development with incremental bundling and file-system caching. Ideal for Next.js 16+ developers seeking faster startup and hot updates.
Plankton-code-quality enforces code quality at write-time, benefiting developers with auto-formatting, linting, and fixes via Claude subprocesses, enhancing overall coding efficiency.
Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders.
# Product Lens — Think Before You Build ## When to Use - Before starting any feature — validate the "why" - Weekly product review — are we building the right thing? - When stuck choosing between features - Before a launch — sanity check the user journey - When converting a vague idea into a spec ...
Spring Security best practices for authn/authz, validation, CSRF, secrets, headers, rate limiting, and dependency security in Java Spring Boot services.
This AI agent skill enables developers to adopt Swift 6.2's concurrency model, ensuring single-threaded code by default and explicit background offloading. It helps resolve data-race safety compiler errors and optimizes app architecture.
This AI agent skill enables Swift developers to write testable code by abstracting external dependencies behind small, focused protocols, leveraging Swift Testing for deterministic results.
Continuous-learning-v2 is an advanced learning system that evolves Claude Code sessions into reusable knowledge, helping developers automate coding tasks through instinct-based behavior extraction and confidence scoring.
# Design System — Generate & Audit Visual Systems ## When to Use - Starting a new project that needs a design system - Auditing an existing codebase for visual consistency - Before a redesign — understand what you have - When the UI looks "off" but you can't pinpoint why - Reviewing PRs that touc...
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
The deployment-patterns skill enables developers to optimize web application deployment workflows using CI/CD pipelines, Docker, and health checks, ensuring production readiness and zero downtime.
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
This AI agent skill provides comprehensive Python testing strategies using pytest, TDD methodology, and best practices, helping developers write robust and maintainable code.
The continuous-learning skill automates pattern extraction from Claude Code sessions, saving developers time and effort. It identifies and saves useful patterns for future use, enhancing AI coding workflows.
This AI agent skill provides best practices for safe and reversible database migrations, benefiting developers working with PostgreSQL, MySQL, and common ORMs. It helps with schema changes, data migrations, and zero-downtime deployments.
This skill provides Nuxt 4 app patterns for hydration safety, performance, and SSR-safe data fetching, benefiting developers with optimized routing and rendering decisions.
The Architecture Decision Records skill helps developers capture and manage architectural decisions made during coding sessions. It auto-detects decision moments, records context, alternatives considered, and rationale, maintaining an ADR log for future reference.
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.
X/Twitter API integration for posting tweets, threads, reading timelines, search, and analytics. Covers OAuth auth patterns, rate limits, and platform-native content posting. Use when the user wants to interact with X programmatically.
The agent-harness-construction skill enhances AI coding by optimizing action spaces, tool definitions, and observation formatting, benefiting developers with higher completion rates.
The iterative-retrieval skill refines context retrieval for subagents, solving the context problem in multi-agent workflows. It benefits developers by progressively refining context.
SwiftUI architecture patterns, state management with @Observable, view composition, navigation, performance optimization, and modern iOS/macOS UI best practices.
The investor-materials AI agent skill helps developers create and update investor-facing documents, ensuring consistency and credibility across pitch decks, one-pagers, and financial models. This skill benefits developers and founders by automating the process of generating investor materials.
AI-first engineering is a skill that helps developers design efficient processes, architectures, and code reviews for AI-assisted code generation, improving overall team productivity and code quality.
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
The skill-creator AI agent skill empowers developers to craft, refine, and perfect skills, streamlining AI coding workflows. It assists in creating new skills, editing existing ones, and evaluating performance for optimal results.
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident ...
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary)...
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
This AI agent skill generates creative, polished code and UI design for web components, pages, and applications, helping developers create production-grade frontend interfaces with exceptional attention to aesthetic details.
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Subagent-driven development automates independent tasks using fresh subagents, ensuring high-quality results and fast iteration for developers. It streamlines AI coding workflows.
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in Node.js and browsers (with WebGPU/WASM) using pre-trained models from Hugging Face Hub.
This skill enables running Python workloads on Hugging Face cloud infrastructure, ideal for developers. It handles data processing, batch inference, experiments, and model training without requiring local GPU/TPU setup.
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.
Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.
Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.
Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.
Stitch Loop is an AI agent skill that enables autonomous frontend builders to iteratively develop websites using Stitch. It integrates pages into site structures and prepares instructions for the next iteration, streamlining AI coding workflows for developers.
The react:components skill transforms Stitch designs into clean, modular React code using system-level networking and AST-based validation, helping frontend engineers streamline their workflow.
The sandbox-sdk AI agent skill enables developers to build secure, isolated code execution environments on Cloudflare Workers, perfect for AI code execution, code interpreters, and CI/CD systems.
Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towa...
This Cloudflare AI agent skill empowers developers to build, secure, and optimize applications with ease, leveraging Workers, Pages, and other Cloudflare technologies. Enhance your development workflow with AI-driven automation.
The component-refactoring skill simplifies high-complexity React components, improving code quality and reducing maintenance efforts for developers. It utilizes patterns and workflows to refactor components, making them more efficient and easier to understand.
Generate Vitest + React Testing Library tests for Dify frontend components, hooks, and utilities. Triggers on testing, spec files, coverage, Vitest, RTL, unit tests, integration tests, or write/review test requests.
Guide for implementing oRPC contract-first API patterns in Dify frontend. Trigger when creating or updating contracts in web/contract, wiring router composition, integrating TanStack Query with typed contracts, migrating legacy service calls to oRPC, or deciding whether to call queryOptions directly vs extracting a helper or use-* hook in web/service.
Warden skill: evaluates first-pass findings and proposes deterministic lint rules that could permanently catch the same patterns. Requires Wardens multi-pass pipeline (phase 2).
Create data-driven presentation slides using React, Vite, and Recharts with Sentry branding. Use when asked to create a presentation, build slides, make a deck, create a data presentation, build a Sentry presentation. Scaffolds a complete slide-based app with charts, animations, and single-file H...
The skill-writer AI agent skill empowers developers to create, synthesize, and iteratively improve agent skills, maximizing high-value input coverage for minimal blind spots in AI coding.
Go back through the previous year of work and create a Notion doc that groups relevant links into projects that can then be documented as SRED projects.
The create-branch AI agent skill automates Git branch creation, following Sentry naming conventions. It benefits developers by saving time and reducing errors, making it an essential tool for efficient coding workflows.
The doc-coauthoring AI agent skill provides a structured workflow for collaborative document creation, benefiting developers and writers. It helps ensure efficient context transfer and refined content through a three-stage process.
The blog-writing-guide skill helps developers create high-quality technical blog posts for the Sentry engineering blog, following specific writing standards and voice. It assists in writing, reviewing, and improving content for a developer audience.
The skill-creator AI agent skill redirects to the canonical sentry-skills:skill-writer workflow, enabling developers to create and update skills efficiently with AI coding.
Helps users discover and install agent skills when they ask questions like how do I do X, find a skill for X, is there a skill that can..., or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
The create-skill AI agent skill automates workflows and integrates APIs for Claude Code, enhancing developer productivity. It teaches the agent focused workflows, leveraging markdown and optional scripts.
Creates GitHub pull requests with properly formatted titles that pass the check-pr-title CI validation. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request.
If This Page Is Close, Keep Narrowing With Adjacent Authority Pages
Do not reset back to the generic directory. Move sideways through these adjacent high-intent collections to narrow the shortlist toward the install path that best matches your team.
Use These Additional Paths If You Need One More Step To Narrow The Decision
These are the supporting surfaces for this collection after the install direction is clear and the primary next paths have already narrowed the decision.