prompt-engineering-suite
Comprehensive prompt engineering with Chain-of-Thought, few-shot learning, prompt versioning, and optimization. Use when designing prompts, improving accuracy, managing prompt lifecycle.
Discover Documentation skills, compare source repositories and read the instructions for each workflow.
Comprehensive prompt engineering with Chain-of-Thought, few-shot learning, prompt versioning, and optimization. Use when designing prompts, improving accuracy, managing prompt lifecycle.
Use when conversation context is too long, hitting token limits, or responses are degrading. Compresses history while preserving critical information using anchored summarization and probe-based validation.
Long-term semantic memory across sessions using Mem0. Use when you need to remember, recall, or forget information across sessions, or when referencing what we discussed last time or in a previous session.
LLM observability platform for tracing, evaluation, prompt management, and cost tracking. Use when setting up Langfuse, monitoring LLM costs, tracking token usage, or implementing prompt versioning.
High-performance LLM inference with vLLM, quantization (AWQ, GPTQ, FP8), speculative decoding, and edge deployment. Use when optimizing inference latency, throughput, or memory.
LLM cost tracking with Langfuse for cached responses. Use when monitoring cache effectiveness, tracking cost savings, or attributing costs to agents in multi-agent systems.
Building MCP (Model Context Protocol) servers for Claude extensibility. Use when creating MCP servers, building custom Claude tools, extending Claude with external integrations, or developing tool packages for...
LangGraph supervisor-worker pattern. Use when building central coordinator agents that route to specialized workers, implementing round-robin or priority-based agent dispatch.
Use when creating or improving golden datasets for AI evaluation. Defines quality criteria, curation workflows, and multi-agent analysis patterns for test data.
CLIP, SigLIP 2, Voyage multimodal-3 patterns for image+text retrieval, cross-modal search, and multimodal document chunking. Use when building RAG with images, implementing visual search, or hybrid retrieval.
Full-power feature implementation with parallel subagents, skills, and MCPs. Use when implementing features, building features, creating features, or developing features.
LangGraph checkpointing and persistence. Use when implementing fault-tolerant workflows, resuming interrupted executions, debugging with state history, or avoiding re-running expensive operations.
Provider-native prompt caching for Claude and OpenAI. Use when optimizing LLM costs with cache breakpoints, caching system prompts, or reducing token costs for repeated prefixes.
Multi-agent frameworks beyond LangGraph. CrewAI crews, Microsoft Agent Framework, OpenAI Agents SDK. Use when building multi-agent systems, choosing frameworks.
文件头三行契约注释。触发:create file、新建文件、编写代码。
Real-time Constitution compliance checker for devflow documents. Blocks partial implementations and hardcoded secrets during file editing.
Use this skill when analyzing an existing codebase with parallel mapper agents, creating codebase documentation, understanding brownfield projects, or mapping code structure. Triggers include "map codebase", "a...
Use this skill when executing small ad-hoc tasks with Kata guarantees, running quick tasks without full planning, or handling one-off work outside the roadmap. Triggers include "quick task", "quick mode", "quic...
Guide for working with the Lexical editor codebase and docs in docs/lexical. Use when implementing or debugging Lexical features: editor state, updates/selection, commands, nodes/serialization, plugins, extensi...
Use this skill when initialize a new project with deep context gathering and project.md. Triggers include "new project", "start project", "initialize project", "create project", "begin project", "setup project"...
Use this skill when surfacing Claude's assumptions about a phase approach before planning, checking what Claude thinks, or validating understanding before planning. Triggers include "list assumptions", "what ar...
Use this skill when switch model profile for kata agents (quality/balanced/budget). Triggers include "set profile", "set profile".
Use this skill when resuming work from a previous session, restoring context after a break, continuing work after /clear, or picking up where you left off. Triggers include "resume work", "continue work", "pick...
Use this skill when showing available Kata commands, displaying the usage guide, explaining command reference, or when the user asks for help with Kata. Triggers include "help", "show commands", "list commands"...
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.