Marketplace
Find the right skill for the job.
Browse the full catalog through outcome-first channels, technical facets, rating filters, and server-side pagination built for a large public marketplace.
data-analysis
Analyze CSV/JSON data with statistics, filtering, and aggregation. Powered by pandas and numpy.
data-engineer
Expert in data pipelines, ETL processes, and data infrastructure
shallow-clone
Imported from https://github.com/opendatahub-io/ai-helpers.
triz
TRIZ systematic innovation methodology with AI-enhanced prompts. Use when: (1) Technical contradiction - improve A but B worsens, (2) Physical contradiction - need opposite properties, (3) Cross-industry solutions via FOS/MOS, (4) Technology evolution prediction, (5) Complex engineering problems. Triggers: "TRIZ", "contradiction", "inventive", "trade-off", "improve without worsening", "ข้อขัดแย้งทางเทคนิค", "innovation breakthrough"
flutter-app-architecture
Provides best practices for Flutter app architecture, including layered architecture, data flow, state management patterns, and extensibility guidelines.
firebase-cloud-functions
Calls Firebase Cloud Functions from Flutter apps. Use when setting up callable functions, passing data to functions, handling errors from function calls, optimizing performance, or testing with the Firebase Emulator Suite.
data-analysis
Comprehensive data analysis skill for CSV files using Python and pandas
firebase-data-connect
Integrates Firebase Data Connect into Flutter apps. Use when setting up Data Connect, designing queries, handling errors, or applying security and performance best practices.
architecture-feature-first
Structures Flutter apps using layered architecture (UI / Logic / Data) with feature-first file organization. Use when creating new features, designing the project structure, adding repositories/services/view models (or cubits/providers/notifiers), or wiring dependency injection. State management agnostic.
firebase-in-app-messaging
Integrates Firebase In-App Messaging into Flutter apps. Use when setting up in-app messaging, triggering or suppressing messages, managing user privacy and opt-in data collection, or testing campaigns.
firebase-database
Integrates Firebase Realtime Database into Flutter apps. Use when setting up Realtime Database, structuring JSON data, querying, performing read/write operations, implementing offline capabilities, or applying security rules.
firebase-analytics
Integrates Firebase Analytics into Flutter apps. Use when setting up analytics, logging events, setting user properties, or configuring event parameters.
ai-development-guide
Technical decision criteria, anti-pattern detection, debugging techniques, and quality check workflow. Use when making technical decisions, detecting code smells, or performing quality assurance.
cursor
Control Cursor AI code editor via CLI. Open files, folders, diffs, and manage extensions.
cats-for-ai
Imported from https://github.com/plurigrid/asi.
ruler
Unified AI agent configuration propagation across 18+ coding assistants.
jira-integration
Agent Skill: Comprehensive Jira integration through lightweight Python scripts. AUTOMATICALLY TRIGGER when user mentions Jira URLs like 'https://jira.*/browse/*', 'https://*.atlassian.net/browse/*', or issue keys like 'PROJ-123'. Use when searching issues (JQL), getting/updating issue details, creating issues, transitioning status, adding comments, logging worklogs, managing sprints and boards, creating issue links, or formatting Jira wiki markup. If authentication fails, offer to configure credentials interactively. Supports both Jira Cloud and Server/Data Center with automatic authentication detection. By Netresearch.
specialist
This skill dynamically enhances existing AI agent teams by adding specialized agents (like Security or Performance experts) based on recurring feedback themes, ensuring non-destructive improvements and targeted problem-solving.
auto-arena
Automatically evaluate and compare multiple AI models or agents without pre-existing test data. Generates test queries from a task description, collects responses from all target endpoints, auto-generates evaluation rubrics, runs pairwise comparisons via a judge model, and produces win-rate rankings with reports and charts. Supports checkpoint resume, incremental endpoint addition, and judge model hot-swap. Use when the user asks to compare, benchmark, or rank multiple models or agents on a custom task, or run an arena-style evaluation.
frontend-ai-guide
Frontend-specific technical decision criteria, anti-patterns, debugging techniques, and quality check workflow. Use when making frontend technical decisions or performing quality assurance.
artifacts-builder
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.
artifacts-builder-aitemplates
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.
evaluation
Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.
Error Recovery
Comprehensive error handling methodology with 13-category taxonomy, diagnostic workflows, recovery patterns, and prevention guidelines. Use when error rate >5%, MTTD/MTTR too high, errors recurring, need systematic error prevention, or building error handling infrastructure. Provides error taxonomy (file operations, API calls, data validation, resource management, concurrency, configuration, dependency, network, parsing, state management, authentication, timeout, edge cases - 95.4% coverage), 8 diagnostic workflows, 5 recovery patterns, 8 prevention guidelines, 3 automation tools (file path validation, read-before-write check, file size validation - 23.7% error prevention). Validated with 1,336 historical errors, 85-90% transferability across languages/platforms, 0.79 confidence retrospective validation.