Agent Skills Hub

systematic-debugging

A rigorous, four-phase methodology to enforce systematic root cause analysis before applying any code fixes.

model-registry-maintainer

Maintain and update the MassGen model registry, including backend capabilities, model metadata, pricing structures, and context window configurations for new and existing AI models.

financial-analyzing

Analyze financial data, calculate key performance metrics like margins and ROI, and generate structured analytical reports.

ui-implementer

Implements UI components from Figma/mockups with pixel-perfect accuracy, intelligent design validation, and adaptive agent switching.

executing-plans

Execute implementation plans in separate sessions with review checkpoints, ensuring task-by-task verification and robust code quality.

receiving-code-review

Rigorous, non-performative code review reception for AI agents, prioritizing technical verification and YAGNI over passive agreement.

jina-cli

A powerful CLI for converting web content and search results into LLM-friendly formats like Markdown, text, or HTML using the Jina AI Reader API.

hive

Automate GitHub issue triage by analyzing reports against the codebase, verifying technical claims, and providing expert-driven responses to resolve invalid issues.

query-sub-agent

Specialized IDF (Information Display Frame) sub-agent for generating and reviewing CQRS Query Side implementations across Java, TypeScript, and Go.

web-search-patterns

Advanced Gemini-powered web search plugin with smart caching, subagent context isolation, and automated query optimization.

implement-feature

Guide for implementing features using architecture-first design, TDD, rich domain models, and Swift 6.2 patterns, ensuring a clean separation between Domain, Infrastructure, and App layers.

python-plan-optimization

6-phase read-only Python analysis workflow that identifies design principle violations, code smells, and modernization opportunities based on specific project types (POC to Open Source).