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SkillsMP는 jeremylongshore/claude-code-plugins-plus-skills에서 3,426개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
jeremylongshore/claude-code-plugins-plus-skills수집된 skill 3,426개 중 40개를 표시합니다.
Explore Kling AI models, versions, and capabilities for video and image generation. Use when selecting models or comparing features. Trigger with phrases like 'kling ai models', 'klingai capabilities', 'kling video models', 'klingai features'.
원문 언어: 영어
Optimize Kling AI for speed, quality, and cost efficiency. Use when improving generation times or finding optimal settings. Trigger with phrases like 'klingai performance', 'kling ai optimize', 'faster klingai', 'klingai quality settings'.
원문 언어: 영어
Understand Kling AI pricing, credits, and cost optimization strategies. Use when budgeting or estimating costs. Trigger with phrases like 'kling ai pricing', 'klingai credits', 'kling ai cost', 'klingai budget'.
원문 언어: 영어
Production readiness checklist for Kling AI integrations. Use before going live or during deployment review. Trigger with phrases like 'klingai production ready', 'kling ai go live', 'klingai checklist', 'deploy klingai'.
원문 언어: 영어
Handle Kling AI API rate limits with backoff and queuing strategies. Use when hitting 429 errors or planning high-volume workflows. Trigger with phrases like 'klingai rate limit', 'kling ai 429', 'klingai throttle', 'kling api limits'.
원문 언어: 영어
Production reference architecture for Kling AI video generation platforms. Use when designing scalable systems. Trigger with phrases like 'klingai architecture', 'kling ai system design', 'video platform architecture', 'klingai production setup'.
원문 언어: 영어
Production SDK patterns for Kling AI: client wrapper, retry logic, async polling, and error handling. Use when building robust integrations. Trigger with phrases like 'klingai sdk', 'kling ai client', 'klingai patterns', 'kling ai wrapper'.
원문 언어: 영어
Download and store Kling AI generated videos in cloud storage (S3, GCS, Azure). Use when persisting videos or building CDN pipelines. Trigger with phrases like 'klingai storage', 'save klingai video', 'kling ai s3 upload', 'klingai cloud storage'.
원문 언어: 영어
Apply artistic styles and visual effects to Kling AI video generation. Use when creating stylized content or using effects API. Trigger with phrases like 'klingai style', 'kling ai effects', 'klingai artistic video', 'stylize klingai video'.
원문 언어: 영어
Configure Kling AI for teams with per-project API keys, usage quotas, and role-based access. Trigger with phrases like 'klingai team', 'kling ai organization', 'klingai multi-user', 'shared klingai access'.
원문 언어: 영어
Generate videos from text prompts with Kling AI. Use when creating videos from descriptions, learning prompt techniques, or building T2V pipelines. Trigger with phrases like 'kling ai text to video', 'klingai prompt', 'generate video from text', 'text2video…
원문 언어: 영어
Migrate between Kling AI model versions safely. Use when upgrading from v1.x to v2.x or adopting new features. Trigger with phrases like 'klingai upgrade', 'kling ai migrate', 'klingai version update', 'upgrade kling model'.
원문 언어: 영어
Build usage analytics and reporting for Kling AI video generation. Use when tracking patterns, analyzing costs, or building dashboards. Trigger with phrases like 'klingai analytics', 'kling ai usage report', 'klingai metrics', 'video generation stats'.
원문 언어: 영어
Extend video duration using Kling AI continuation. Use when creating longer videos from shorter clips or building sequences. Trigger with phrases like 'klingai extend video', 'kling ai video continuation', 'klingai longer video', 'extend klingai clip'.
원문 언어: 영어
Configure webhook callbacks for Kling AI task completion. Use when building event-driven pipelines or replacing polling. Trigger with phrases like 'klingai webhook', 'kling ai callback', 'klingai notifications', 'video completion webhook'.
원문 언어: 영어
Wire LangChain 1.0 / LangGraph 1.0 tests into a GitHub Actions pipeline — unit tests with FakeListChatModel, VCR-gated integration tests, warning-filter policy, and eval-regression merge gates. Complements langchain-local-dev-loop (F23) which covers the inner…
원문 언어: 영어
Paste-match catalog of 14 real LangChain 1.0 / LangGraph 1.0 exceptions with named causes and named fixes, plus a triage decision tree. Use when you have a traceback and want the specific fix, not speculative documentation. Covers ImportError (0.2/0.3 → 1.0…
원문 언어: 영어
Works correctly with LangChain 1.0's typed content blocks on AIMessage.content — text, tool_use, image, thinking, document — across Claude, GPT-4o, and Gemini, including multi-modal composition and tool-call iteration. Use when composing multi-modal messages,…
원문 언어: 영어
Compose LangChain 1.0 chains with RunnableParallel, RunnableBranch, RunnablePassthrough.assign, and RunnableLambda — correct input/output shapes, debug probes, and typed composition that catches dict-shape bugs before invocation. Use when wiring multi-step…
원문 언어: 영어
Control LangChain 1.0 AI spend with accurate streaming token accounting, model tiering, provider-specific cache hit tuning, per-tenant budgets, and retry dedup. Use when AI spend grows faster than traffic, a cost regression lands, or you need per-tenant…
원문 언어: 영어
Load and chunk documents for LangChain 1.0 RAG pipelines correctly — language-aware splitters, table-safe PDF loaders, Cloudflare-compatible web loaders, chunk-boundary strategies that survive real-world structure. Use when building a RAG pipeline, diagnosing…
원문 언어: 영어
Produce a reproducible, sanitized diagnostic bundle for a LangChain / LangGraph incident — environment snapshot, version manifest, filtered astream_events(v2) transcript, propagating callback stack, LangSmith trace URL — so a debug colleague can reproduce the…
원문 언어: 영어
Build a LangGraph 1.0 Deep Agent — planner + subagents + virtual filesystem + reflection loop — without the state-growth and prompt-inheritance traps. Use when building a long-horizon agent that must plan, delegate subtasks, work against a scratchpad…
원문 언어: 영어
Deploy a LangChain 1.0 / LangGraph 1.0 app to Cloud Run, Vercel, or LangServe correctly — timeouts sized for chain length, cold-start mitigation, SSE anti-buffering headers, Secret Manager over `.env`. Use when prepping first prod deploy, debugging a stream…
원문 언어: 영어
Build and query vector stores with LangChain 1.0 without getting burned by flipped score semantics, embedding-dim mismatches, reranker quirks, and chunk-splitter bugs. Use when building a RAG pipeline, choosing between FAISS / Pinecone / Chroma / PGVector,…
원문 언어: 영어
Enforce tenant isolation and role-based access across LangChain 1.0 chains and LangGraph 1.0 agents — per-request retriever construction, tenant-scoped rate limits, role-scoped tool allowlists, and structured audit logs. Use when building multi-tenant saas,…
원문 언어: 영어
Build reproducible evaluation pipelines for LangChain 1.0 chains and LangGraph 1.0 agents — golden datasets, LangSmith evaluate(), ragas RAG metrics, deepeval LLM-as-judge, agent trajectory analysis, and CI gating on quality regressions. Use when setting up…
원문 언어: 영어
Triage LangChain 1.0 / LangGraph 1.0 production incidents — LLM-specific SLOs, provider outage runbook, latency spike decision tree, cost-overrun response, agent loop containment. Use during an on-call page, in a post-mortem, or writing the team's first LLM…
원문 언어: 영어
Build a correct LangGraph 1.0 ReAct agent with `create_react_agent` — typed tools, error propagation, recursion caps, and stop conditions that actually stop. Use when writing your first tool-calling agent, migrating from `AgentExecutor` / `initialize_agent`,…
원문 언어: 영어
Build a correct LangGraph 1.0 StateGraph — typed TypedDict state with reducers, nodes, edges, compile, and recursion budgets — without hitting the silent-termination and state-replacement traps. Use when writing your first LangGraph StateGraph, diagnosing why…
원문 언어: 영어
Persist LangGraph agent state correctly with MemorySaver and PostgresSaver — thread_id discipline, JSON-serializable state rules, time-travel, schema migration. Use when adding chat memory, migrating from ConversationBufferMemory, or time-traveling an agent…
원문 언어: 영어
Build LangGraph 1.0 human-in-the-loop approval flows with `interrupt_before` / `interrupt_after` and `Command(resume=...)` — JSON-serializable state, clean resume semantics, and UI wiring for approval decisions. Use when adding an approval gate before an…
원문 언어: 영어
Pick the correct LangGraph 1.0 stream_mode ("messages" vs "updates" vs "values"), wire it into SSE or WebSocket without proxy-buffering gotchas, and filter astream_events(v2) server-side before forwarding to the browser. Use when building a live-token chat…
원문 언어: 영어
Compose LangGraph 1.0 subgraphs correctly — shared state key propagation, Send / Command(graph=...) dispatch, callback scoping, per-subgraph recursion budgets, and testing each subgraph in isolation. Use when building a planner + executor, a nested agent…
원문 언어: 영어
Build a fast, deterministic local test loop for LangChain 1.0 / LangGraph 1.0 — FakeListChatModel fixtures, pytest config, VCR cassettes with key redaction, warning-filter policy. Use when adding tests to a new chain, fixing a flaky test, or making…
원문 언어: 영어
Build composable middleware for LangChain 1.0 chains and LangGraph 1.0 agents — PII redaction, caching, retry, token budgets, guardrails — with ORDERING rules that avoid cache-key leakage and double-counting. Use when adding cross-cutting behavior, hardening…
원문 언어: 영어
Invoke Claude, GPT-4o, and Gemini through LangChain 1.0 without tripping on the content-block, token-accounting, and structured-output quirks that silently break production code. Use when initializing chat models, routing across providers, iterating AIMessage…
원문 언어: 영어
Build reliable dev / staging / prod isolation for LangChain 1.0 services — Pydantic `Settings` + `SecretStr`, cloud Secret Manager in prod, per-env prompt and model version pinning, env-specific checkpointer and observability. Use when graduating from…
원문 언어: 영어
Wire LangSmith tracing and custom metric callbacks into a LangChain 1.0 chain or LangGraph 1.0 agent correctly — env-var spelling, subgraph propagation, per-tenant dimensions, cost and latency counters. Use when setting up observability on a new service,…
원문 언어: 영어
Wire LangChain 1.0 / LangGraph 1.0 traces into an OpenTelemetry-native backend (Jaeger, Honeycomb, Grafana Tempo, Datadog) with LLM-specific SLOs, safe prompt-content policy, and subgraph-aware span propagation. Use when LangSmith is not the right fit…
원문 언어: 영어