memorystore-config

api-testing-helper

openapi-spec-generator

integration-test-generator

design-doc-template

incident-postmortem-template

migration-guide-creator

email-template-generator

kpi-dashboard-template

stakeholder-communication-template

test-skill

schema-optimization-orchestrator

Run tests in mflux (fast/slow/full), preserve image outputs, and handle golden image diffs safely.

Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.

Turn a conversation into an issue that still reads correctly after a

Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.

Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.

Track session costs, set budget alerts, and optimize token spend. Use to check costs mid-session or set spending limits.

Remove AI-generated code slop, unnecessary comments, and over-engineering from the current branch diff. Cleans up boilerplate, simplifies abstractions, and strips defensive code. Use when cleaning up code, simplifying, removing boilerplate, or before committing.

Show session analytics, learning patterns, correction trends, heatmaps, and productivity metrics. Computes stats from project memory and session history. Use when asking for stats, statistics, progress, how am I doing, coding history, or dashboard.

Capture a lesson from the current session into permanent memory.

LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.

Audit connected MCP servers for token overhead, redundancy, and security. Use when sessions feel slow or before adding new MCPs.

Create and manage git worktrees for parallel coding sessions with zero dead time. Use when blocked on tests, builds, wanting to work on multiple branches, context switching, or exploring multiple approaches simultaneously.

Analyze permission denial patterns and generate optimized alwaysAllow and alwaysDeny rules. Use when permission prompts are slowing you down or after sessions with many denials.

Stress-test a plan by walking its decision tree one question at a time. Use when the user wants to pressure-test a design before implementation.

Complete AI coding workflow system. Orchestration patterns, 18 hook events, 5 agents, cross-agent support, reference guides, and searchable learnings. Works with Claude Code, Cursor, and 32+ agents.

Like muscle memory for your coding sessions. Find and surface relevant learnings before you start working.

Use when saying "commit", "save changes", or ready to commit after making changes.

Reduce token waste by 40-60% through anti-sycophancy rules, tool-call budgets, one-pass coding, task profiles, and read-before-write enforcement. Inspired by drona23/claude-token-efficient.

End your coding session with intention.

Adapt and debug existing or new models for vLLM on Ascend NPU. Implement in /vllm-workspace/vllm and /vllm-workspace/vllm-ascend, validate via direct vllm serve from /workspace, and deliver one signed commit in the current repo.

Enhance your AI coding agent with knowledge about AI Elements.

Fetch the latest financial signals and transmission-chain analyses from DeepEar Lite. Use when the user needs immediate insights into financial market trends, stock performance factors, and reasoning from the DeepEar Lite dashboard.

Market prediction skill using Kronos. Use when user needs finance market time-series forecasting or news-aware finance market adjustments.

Search A-Share/HK/US finance stock tickers and retrieve finance stock price history. Use when user asks about finance stock codes, recent price changes, or specific company finance stock info.

Profile application performance, identify bottlenecks, design optimization strategies, implement changes, benchmark improvements, and review code quality.

Create custom tools, toolkits, and MCP integrations for Neuron AI agents. Use this skill when the user mentions creating tools, building toolkits, extending Tool class, defining tool properties, implementing tool execution, MCP server integration, Model Context Protocol, connecting external tools, or tool guidelines. Also trigger for any task involving ToolProperty, ArrayProperty, ObjectProperty, AbstractToolkit, McpConnector, or StdioTransport/SseHttpTransport/StreamableHttpTransport.

Systematic UX improvement pipeline: scan -> diagnose -> design -> implement -> test. Built on **team-worker agent architecture** — all worker roles share a single agent definition with role-specific P

Automates interactions for Apple-platform apps (iOS, tvOS, macOS) and Android devices. Use when navigating apps, taking snapshots/screenshots, tapping, typing, scrolling, extracting UI info, or collecting logs, network inspection, and perf snapshots across mobile, TV, and desktop targets.

Run, optimize, and debug OpenVMM fuzzers. Covers cargo-fuzz targets, crash reproduction, lldb debugging, code coverage analysis, entropy optimization, and multi-target parallel campaigns.

Investigate CI failures on OpenVMM PRs. Load when a PR has failing CI checks, you need to download and analyze test artifacts, or you need to diagnose build, fmt, clippy, or VMM test failures.

Run VMM tests locally with cargo xflowey vmm-tests-run. Load when running or debugging VMM tests, or when you need to understand the petri test framework, artifact handling, or cross-compilation for VMM tests.

Analyze configuration files for validation and best practices

A test skill with prompt injection patterns

A clean skill with no security issues.

Formats text according to specified style guidelines. A clean example skill with no security issues.

Modern web development standards based on Lighthouse best practices audits. Covers security, browser compatibility, and code quality patterns.

Deep performance optimization based on Lighthouse performance audits. Focuses on loading speed, runtime efficiency, and resource optimization.

Comprehensive quality review based on Google Lighthouse audits. Covers Performance, Accessibility, SEO, and Best Practices across 150+ checks.