kradleverse:init
Register an agent on kradleverse
init-first-agent
Walk the operator through creating the first NanoClaw agent for a DM channel — resolve the operator's channel identity, wire the DM messaging group to a new agent, and trigger a welcome DM via the normal delivery path. Use after channel credentials are configured and the service is running.
inits
Analyze a codebase and create or improve an AGENTS.md file for future agent instances. Use when onboarding to a repository and capturing hard-to-rediscover conventions, constraints, and rationale.
inquire
Request clarification when input is ambiguous. Use when user request has missing parameters, conflicting interpretations, or insufficient constraints for reliable execution.
instantly-ai
Talk to Instantly Ai Founders about their expertise. Instantly Ai Founders provides authentic advice using their mental models, core beliefs, and real-world examples.
intent-first
Clarify user intent before executing tasks. Use when requests are vague, ambiguous, or could be interpreted multiple ways. Helps prevent wasted effort from misunderstanding.
intent
Turn rough ideas into clear work orders before planning or building. Use when request is vague like "add a button", "make it better", "fix the thing". Triggers on ambiguous or underspecified requests. Produces a brief with scope, acceptance criteria, and stop conditions.
interaction-guidelines
ユーザーとの効果的な対話パターン、質問生成、曖昧さ解消、合意形成、ユーザー負担軽減のガイドラインを定義する。ユーザーに質問する際、要件を確認する際、フィードバックを収集する際、またはユーザーが対話改善、質問方法、確認プロセス、Progressive Disclosureに言及した際に使用する。
interactor-agents
Create LLM-powered AI assistants with tools and data sources through Interactor. Use when building conversational AI, chatbots, tool-calling assistants, or agents that need to query databases and external APIs.
investigate-before-acting
Mandatory protocol that prevents AI agents from fabricating information. Forces best practice search before every action — coding, design, content, pricing, naming, architecture, everything. Every decision must have a citation (source name + URL + direct quote). Based on Anthropic official hallucination reduction techniques.
invoke-opencode-acp
Delegate complex tasks to OpenCode subagent, use when >=2 file modifications or batch operations
jules-cli
Interact with the Jules CLI to manage asynchronous coding sessions. Use this skill to assign tasks, monitor progress, and pull patches from completed sessions.
jules
Delegate coding tasks to Google Jules AI agent for asynchronous execution. Use when user says: 'have Jules fix', 'delegate to Jules', 'send to Jules', 'ask Jules to', 'check Jules sessions', 'pull Jules results', 'jules add tests', 'jules add docs', 'jules review pr'. Handles: bug fixes, documentation, features, tests, refactoring, code reviews. Works with GitHub repos, creates PRs.
kagent
Kubernetes-native AI agent framework for building, deploying, and managing AI agents on Kubernetes. This skill should be used when deploying AI agents as Kubernetes resources, analyzing cluster health with AI, and automating complex K8s operations. Use this skill for Phase IV advanced AIOps and agent-based cluster management.
kagenti
Deploy and manage Kagenti platform, operator, agents, and tools on Kubernetes.
kata-set-profile
Switch model profile for kata agents (quality/balanced/budget). Triggers include "set profile", "set profile".
kit-agent-development
(ePost) This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
kitt-create-subagents
Expert guidance for creating, building, and using Claude Code subagents and the Task tool. Use when working with subagents, setting up agent configurations, understanding how agents work, or using the Task tool to launch specialized agents.
koerner-office
Talk to Koerner Office King Of Hustle about their expertise. Koerner Office King Of Hustle provides authentic advice using their mental models, core beliefs, and real-world examples.
konstantinos
Talk to Konstantinos Doulgeridis Youtuber about their expertise. Konstantinos Doulgeridis Youtuber provides authentic advice using their mental models, core beliefs, and real-world examples.
kramme:agents-md
This skill should be used when the user asks to "update AGENTS.md", "add to AGENTS.md", "maintain agent docs", or needs to add guidelines to agent instructions. Guides discovery of local skills and enforces structured, keyword-based documentation style.
langchain-agent
AI agent with tools (search, calculator) using LangGraph and AI SDK.
langchain-agents
Create and use LangChain agents with createAgent - includes agent loops, ReAct pattern, tool execution, and state management
langchain-human-in-the-loop
Add human oversight to LangChain agents using HITL middleware - includes interrupts, approval workflows, edit/reject decisions, and checkpoints
langchain-react-agent
LangChain ReAct agent implementation with tool binding for reasoning and action loops
langchain-retrieval-agent
AI agent with retrieval tool for document Q&A using RAG and LangGraph.
mastering-langgraph
Build stateful AI agents and agentic workflows with LangGraph in Python. Covers tool-using agents with LLM-tool loops, branching workflows, conversation memory, human-in-the-loop oversight, and production monitoring. Use when - (1) building agents that use tools and loop until task complete, (2) creating multi-step workflows with conditional branches, (3) adding persistence/memory across turns with checkpointers, (4) implementing human approval with interrupt(), (5) debugging via time-travel or LangSmith. Covers StateGraph, nodes, edges, add_conditional_edges, MessagesState, thread_id, Command objects, and ToolMessage handling. Examples include chatbots, calculator agents, and structured workflows.
langgraph-architecture
Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and streaming approaches.
langgraph-checkpoints
LangGraph checkpointing and persistence. Use when implementing fault-tolerant workflows, resuming interrupted executions, debugging with state history, or avoiding re-running expensive operations.
langgraph-code-review
Reviews LangGraph code for bugs, anti-patterns, and improvements. Use when reviewing code that uses StateGraph, nodes, edges, checkpointing, or other LangGraph features. Catches common mistakes in state management, graph structure, and async patterns.
langgraph-development-skill
'CRITICAL: LangGraph workflows are NestJS applications under apps/langgraph/.
langgraph-functional
LangGraph Functional API with @entrypoint and @task decorators. Use when building workflows with the modern LangGraph pattern, enabling parallel execution, persistence, and human-in-the-loop.
langgraph-fundamentals
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
langgraph-graph-api
使用 StateGraph、节点、边、START/END 节点和 Command API 构建图，结合控制流与状态更新
langgraph-hitl
Human-in-the-loop integration for LangGraph workflows with approval and intervention points
langgraph-human-in-loop
LangGraph human-in-the-loop patterns. Use when implementing approval workflows, manual review gates, user feedback integration, or interactive agent supervision.
langgraph-human-in-the-loop
INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.
langgraph-implementation
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
langgraph-interrupts
人机交互与动态中断和断点：暂停执行以供人工审查和使用 Command 恢复
langgraph-overview
理解 LangGraph：用于构建有状态、长期运行 Agent 的低级编排框架，具有持久执行、流式传输和人机交互能力
langgraph-parallel
LangGraph parallel execution patterns. Use when implementing fan-out/fan-in workflows, map-reduce over tasks, or running independent agents concurrently.
LangGraph Patterns Expert
Build production-grade agentic workflows with LangGraph using graph-based orchestration, state machines, human-in-the-loop, and advanced control flow
langsmith-agent-builder
LangSmith Agent Builder - No-code platform for creating AI agents with built-in tools (Gmail, Slack, GitHub, Linear), OAuth integrations, MCP server support, Slack deployment, and programmatic invocation via LangGraph SDK
latent-space-engineering
Shapes agent behavior via instruction framing and style transfer. Use when composing dispatch prompts or writing skill instructions for parallel review agents.
launch
Start a Space-Agents session. Displays welcome screen with project status.
lead-project
Autonomous technical lead. Takes commander's intent and drives a project to completion through an OODA loop over implementation, refactoring, review, and bug-hunting skills. Has broad authority — creates tickets, commits, invokes any skill — and only escalates via andon cord for irreversible actions, public releases, or genuinely blocking decisions. User acts as product owner; skill acts as tech lead.
learn
Runs the learning cycle on all LearningAgent sessions with pending transcripts. Identifies issues, investigates root causes, and incorporates learnings into agent definitions.
learning-agents
Dispatch entry point for the LearningAgents plugin. Routes to sub-commands for creating agents, running learning cycles, and reporting issues.
phi-ain-v2
ΦAIN v2.0: Φ-Aetheric Information Nexus. Master cognitive architecture. Auto-boots trinity + phase-boundary-detector + full tier cascade. Load THIS to load EVERYTHING.
letta
Letta framework for building stateful AI agents with long-term memory. Use for AI agent development, memory management, tool integration, and multi-agent systems.
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