nuvel
nuvel에는 Folken2에서 수집한 skills 28개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
Use when the user wants to build a Google ADK agent — scaffolding a new agent, adding tools/skills/prompts to one, or asking how to structure an ADK project. Triggers on phrases like "create an ADK agent", "build a Google agent", "scaffold an agent", "make an agent that does X", "I need an ADK skeleton", or any task involving generated-agents/, LlmAgent, SkillToolset, or the ADK framework. Also use whenever the user mentions `nuvel`, the `nuvel` CLI, or asks about agent architecture patterns / callbacks / HITL / streaming / ADK prompt engineering — nuvel ships the canonical knowledge skills for those topics. Lean toward triggering — if the task touches Google ADK at all, this skill is in scope.
Delegate work to sub-agents with the ADK 2.0 Task API — `mode='task'`, `mode='single_turn'`, `mode='chat'` on `LlmAgent`, the auto-attached `finish_task` tool, and typed contracts via `input_schema` / `output_schema`. Load this skill when one agent needs to hand a bounded unit of work to another and get a validated result back, or when migrating off SequentialAgent / ParallelAgent / LoopAgent.
Creating valid SKILL.md files following the agentskills.io specification — frontmatter, instructions, references directory, progressive disclosure (L1/L2/L3), and SkillToolset wiring in agent.py. Load this skill when generating domain skills for an agent.
Build graph-based agents with ADK 2.0 `Workflow` — declare nodes and edges, route conditionally, fan-out/fan-in in parallel, run dynamic nodes at runtime, and add human-in-the-loop revision cycles. Load this skill whenever the agent needs anything beyond a strictly linear or trivially parallel pipeline.
Agent architecture patterns for Google ADK 2.0 — when to reach for a single LlmAgent, a Workflow graph (new default for multi-step orchestration), or the shortcut classes SequentialAgent / LoopAgent / ParallelAgent. Load this skill when deciding the agent's top-level shape.
Pattern for turning a brief into a coherent deck outline — intent detection, section ratios, draft headings, expansion
When and how to suggest reordering, splitting, or trimming a deck — agenda placement, CTA placement, problem-solution arc, methodology-results arc
Rubric for sharpening the active slide — parallelism, bullet count, length, title strength, notes-vs-bullets separation
How to learn the user's deck style from kept slides and when to consolidate fingerprints into a tight rulebook
How to rewrite a selected passage per the user's instruction without silently expanding scope, breaking length, or losing quoted material
How to learn and refine the user's writing style from passages they keep after agent edits, and when to consolidate fingerprints into a tight rulebook
How to draft new Word sections and extensions that sound like the user, using the style memory and the document context
Rubric for giving honest, specific, voice-aware feedback on the user's draft emails
How to search the user's Outlook mailbox effectively using Composio's OUTLOOK_* tools, including query planning and result ranking
How to learn and refine the user's writing style from their sent emails, and when to consolidate fingerprints into a tight rulebook
How to draft email replies and new messages that sound like the user, using the style memory
The Composio Tool Router for ADK agents — the --with-composio scaffold flag, per-user sessions via composio.create(user_id=...), the McpToolset wiring, multi-tenant patterns, and when not to reach for it. Read when an ADK agent needs broad integration coverage (Gmail, GitHub, Slack, Notion, Calendar, Linear, etc.) without authoring per-service tools, when the user wants ~1000 toolkits behind one endpoint, or when adding multi-tenant credential isolation to an agent.
Deploying a Managed Agents project to production — wrapping the SDK in FastAPI with SSE, the env vars that have to be set, agent-version pinning, bearer auth, cost tracking via span events, and Docker/Railway/Fly. Read when going from "setup.py worked locally" to "it's running on a server", when designing the request/response contract, when investigating why deployments lose state, or when planning rollouts of agent updates.
The event stream model for Anthropic Managed Agents — stream-first ordering, the idle-break gate, lossless reconnect via consolidation, custom-tool round-trip, and the most-common event types. Read when implementing or debugging the orchestrator loop, when sessions hang or terminate prematurely, or when reconnecting a dropped SSE stream.
The mandatory flow for Anthropic Managed Agents — create a versioned agent once, reference it from sessions on every run. Read first when starting a Managed Agents project, when migrating from a different Anthropic surface (Claude API, Claude Agent SDK), or when confused about why session.create() rejects model/system/tools fields.
Skills and memory stores in Anthropic Managed Agents — Anthropic prebuilt skills (xlsx/docx/pptx/pdf), custom skills via the Skills API, and memory stores for cross-session persistence with versioning and audit. Read when adding domain expertise the agent should auto-load, when the agent needs persistent state across sessions, or when distinguishing memory from session resources.
The three kinds of tools in Anthropic Managed Agents — the prebuilt agent toolset (`agent_toolset_20260401`), MCP toolsets with vault-backed credentials, and custom tools handled host-side. Read when adding a new capability to your agent, when deciding where to put a third-party API call, when a third-party service has a hosted MCP server, or when an integration needs an API key.
Deploying Claude Agent SDK agents to production — wrapping the SDK in FastAPI with SSE streaming, session resume, cost tracking via ResultMessage, Docker/Railway/Fly config, ANTHROPIC_API_KEY handling, and bearer-auth patterns. Read when going from "it works locally" to "it's running on a server", when designing the request/response contract for an agent endpoint, or when investigating why deployments are slower or more expensive than expected.
Hooks in the Claude Agent SDK — PreToolUse, PostToolUse, UserPromptSubmit, Stop event types, the HookMatcher signature, hook function signatures, blocking vs auditing patterns, and when hooks beat permission callbacks. Read when adding deterministic guards around tool calls, when implementing audit logging, when injecting context dynamically, or when can_use_tool isn't enough.
Wiring external MCP servers into a Claude Agent SDK agent — stdio and HTTP transports, dict format, when to use SDK MCP vs external, naming conventions, and common pre-built servers (filesystem, fetch, sequential-thinking). Read when you need to give Claude access to a service via an existing MCP server, when choosing between writing your own tools and consuming an external one, or when debugging "tool not found" errors.
The Claude Agent SDK permission model — allowed_tools, disallowed_tools, the six permission_mode values, and the can_use_tool callback. Read when designing what an agent is allowed to do, when production deploys are surprising users with permission prompts, when you want dynamic per-call gating, or when locking down a deploy that runs unattended.
System prompts in the Claude Agent SDK — string vs file vs preset, the claude_code preset and its append field, dynamic prompts via per-turn rebuilding, and how setting_sources composes user/project/local instructions. Read when designing the agent's voice and operating principles, when migrating an existing prompt into the SDK shape, or when choosing between a static and a dynamic prompt.
Building custom tools for Claude Agent SDK agents — the @tool decorator, schema dicts, return shape, error returns, and the mcp__server__tool naming gotcha. Read when adding a new tool to a Claude Agent SDK project, when you need to expose Python functions to Claude, or when designing tool boundaries.