482 skills · sorted by relevance
Design service mesh observability — distributed tracing, service-level metrics, and dashboards. Use when asked to "add service mesh observability", "set up distributed tracing in the mesh", or "build service-level dashboards".
The English summary is being prepared. Showing the original description.
Distributed storage systems design and operation for cloud platforms. Covers the GFS/HDFS block-and-master pattern, object storage (Swift/S3) with consistent hashing and eventual consistency, block storage semantics, replication vs erasure coding, the CAP theorem in practice, read-repair and anti-entropy, snapshot chains, and the GFS/BigTable/Spanner evolution. Use when designing a storage subsystem, choosing between object/block/file, or reviewing a replication and consistency strategy.
The English summary is being prepared. Showing the original description.
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
The English summary is being prepared. Showing the original description.
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
The English summary is being prepared. Showing the original description.
Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.
The English summary is being prepared. Showing the original description.
Guide for using Simba 5, the JVM leader-election and distributed-lock library, in applications. Use when adding leader election, leader-only work (runWhileLeader, schedule, @SimbaScheduled), partitioned work (group, @SimbaPartitioned), distributed locks (lock / LockTerm), configuring the JDBC (MySQL, PostgreSQL), Redis or Zookeeper backend, integrating with Spring Boot, using fencing tokens, tuning session timing, or migrating from Simba 4.x. For test-focused work, use the simba-testing skill as well.
The English summary is being prepared. Showing the original description.
Work with the @upstash/redis TypeScript/JavaScript SDK, a serverless HTTP-based Redis client for Next.js, Vercel, Cloudflare Workers, edge runtimes, and Node.js. Use when adding a cache (cache-aside, write-through, TTL and expiration strategies), session storage and user sessions, a key-value store, leaderboards and rankings with sorted sets, counters, distributed locks, queues with lists, streams and consumer groups, sparse index-addressed arrays and ring buffers (ARSET, ARINSERT, ARRING, ARGREP, AROP), embeddings and nearest-neighbour vector search stored inside Redis (VECTOR commands via redis.vector, separate from @upstash/vector), JSON documents, pipelines and MULTI/EXEC transactions, Lua scripting, read replicas, or full-text search, typo-tolerant search, facets, aggregations, and search over Redis stream entries with Upstash Redis Search (different from regular FT.SEARCH; also available for TCP clients via @upstash/search-redis and @upstash/search-ioredis). Also use when migrating from ioredis or node-redis, when a Redis connection is needed from a serverless function without connection pooling, when integrating @upstash/ratelimit, or when the user says Redis cache, KV store, session store, serverless Redis, or Upstash Redis. Also use when building AI agents on Redis with Upstash AgentKit (agent memory, chat history, RAG tools, tool caching, chat persistence, resumable streams, distributed locks) for the Vercel AI SDK, TanStack AI, or Vercel Eve. Supports automatic serialization/deserialization of JavaScript types.
The English summary is being prepared. Showing the original description.
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
The English summary is being prepared. Showing the original description.
"Explain blockchain fundamentals including distributed ledger architecture, consensus mechanisms, and block structure. Use this skill when the user needs to understand blockchain concepts, evaluate whether blockchain fits a use case, or design a blockchain-based solution — even if they say 'how does blockchain work', 'do I need blockchain', or 'distributed ledger'.".
The English summary is being prepared. Showing the original description.
Use this skill when the user is working with an Aspire distributed application and needs to operate the AppHost or its resources through the Aspire CLI: start, restart, stop, or wait on the app; inspect resources, logs, traces, docs, or health; add integrations; manage secrets or config; publish, deploy, or rerun a named pipeline step; initialize Aspire in an existing app; recover missing `.modules` files in a TypeScript AppHost; discover the right frontend URL for Playwright from Aspire state; expose custom dashboard/resource commands; or understand unfamiliar Aspire AppHost APIs in C# or TypeScript. Use it even if they describe the task in terms of an AppHost, resources, dashboard, existing app bootstrap, missing generated modules, Playwright URL discovery, C# API understanding, or local distributed app workflow without explicitly naming Aspire. Do not use it for non-Aspire .NET apps, container-only repos with no AppHost, or ordinary build and test tasks.
The English summary is being prepared. Showing the original description.
Comprehensive reference for inter-process communication mechanisms -- every way processes can talk on a computer. Covers sockets (TCP, UDP, Unix domain), WebSockets, SSE, pipes (named/anonymous), shared memory (mmap, shm_open), message queues, signals, D-Bus, XPC (macOS), gRPC, REST, stdin/stdout, file-based coordination, and clipboard. Performance benchmarks, platform availability, and code examples for each. Special focus on which IPC works best for AI agent coordination. Activate on: "IPC", "inter-process communication", "process communication", "how do I talk between processes", "Unix socket vs TCP", "shared memory", "named pipe", "WebSocket vs SSE", "gRPC vs REST", "agent coordination IPC", "XPC service", "message passing", "stdout pipe", "D-Bus", "mmap". NOT for: distributed systems design (use distributed-systems), network protocol design (use networking), message queue infrastructure like Kafka (use data-pipeline-engineer).
The English summary is being prepared. Showing the original description.
Implementing distributed tracing with W3C Trace Context — the byte-precise `traceparent` and `tracestate` header formats, OpenTelemetry's W3CTraceContextPropagator as the modern default (replacing X-B3-* and X-Datadog-*), head vs tail sampling, and HTTP→SQL trace propagation via sqlcommenter. Grounded in the W3C REC and OpenTelemetry specs.
The English summary is being prepared. Showing the original description.
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
The English summary is being prepared. Showing the original description.
Fornece treinamento distribuído de LLM nativo do PyTorch usando torchtitan com paralelismo 4D (FSDP2, TP, PP, CP). Use para fazer pré-treinamento de Llama 3.1, DeepSeek V3 ou modelos customizados em escala de 8 a 512+ GPUs com Float8, torch.compile e checkpoint distribuído.
The English summary is being prepared. Showing the original description.
Cloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when choosing architecture patterns for reliability, performance, messaging, or security in a distributed cloud system.
The English summary is being prepared. Showing the original description.
Correlate events across multiple log files from different sources, systems, or time periods. Build unified timelines, identify causal relationships between events, and highlight anomalies that span multiple data sources. Supports timezone normalization and gap detection. Use when analyzing logs from multiple systems (frontend, backend, database, infrastructure), investigating distributed system failures, or building event timelines across services. Triggers: "correlate these logs", "build timeline from multiple logs", "cross-system analysis", "find related events across logs", "multi-source log analysis", "distributed trace analysis"
The English summary is being prepared. Showing the original description.
Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.
The English summary is being prepared. Showing the original description.
Expert en systèmes distribués v2 (CAP, consensus, partitions, consistence événuelle, patterns)
The English summary is being prepared. Showing the original description.
Expert en systèmes distribués (CAP theorem, consensus, partitions, vector clocks)
The English summary is being prepared. Showing the original description.
Expert en CockroachDB (distributed SQL, geo-partitioning, serializable, multi-region)
The English summary is being prepared. Showing the original description.
Caching specialist v2 — Redis, Memcached, CDN caching, invalidation strategies, distributed, patterns
The English summary is being prepared. Showing the original description.
Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.
The English summary is being prepared. Showing the original description.
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
The English summary is being prepared. Showing the original description.
High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
The English summary is being prepared. Showing the original description.