Skills tagged multi-agent: 15 agent skills for Claude Code

• agents-build — Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments.
• app-platform-sandbox — Create and manage isolated container sandboxes for AI agent code execution.
• chaos-engineer — Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks.
• claude-switch-models-setup — 7, GLM, DeepSeek, StepFun, Anthropic) in separate terminal windows at the same time.
• coordinating-multi-space-devops-agent — Coordinate the AWS DevOps Agent across multiple AgentSpaces from one Claude Code session — route questions to the right space (prod vs staging vs knowledge).
• daymade-sector-research — A股行业投研工作流：全板块 Top N 涨幅标的计算、公告窗口检索（周/月）、市场情绪证据分级判断，并以 Agent Team 并行执行 + fresh-context 对抗验证。 触发场景（命中任一即读本 skill）： - 「XX 行业 Top N / Top 10 标的」（如「医药行业今天的 Top 10.
• latent-briefing — This skill should be used when the user asks to "share memory between agents", "KV cache compaction for multi-agent", "orchestrator worker context".
• libafl — Builds custom fuzzers with LibAFL, the modular Rust fuzzing library.
• local-codex — Launch and manage OpenAI Codex CLI (local agent) as a non-interactive coding sub-agent. 5 agent capabilities through local CLI.
• local-conversation-history — Entry point for local AI conversation history across providers.
• marketing-council — When the user wants multiple expert perspectives on a marketing question — a simulated board of advisors staffed by legendary marketers (Seth Godin.
• peer-message — Bridge local Claude Code and Codex sessions only when the current host's native communication tools do not cover the target.
• product-analysis — Multi-path parallel product analysis with cross-model test-time compute scaling.
• seo-profound — Profound LLM citation tracker (extension). Time-series brand citation rates across ChatGPT, Perplexity, and other LLMs.
• stitch-loop — Teaches agents to iteratively build websites using Stitch with an autonomous baton-passing loop pattern