Results for “provisioning-profiles”

Build and maintain a structured personal-context portfolio for the project owner — identity, working style, goals, team, decision patterns. Includes both an interview protocol for bootstrapping and observable-signal patterns for incremental refinement. Use to bootstrap an owner profile (interview), to refine an existing profile (target one file), or to incrementally update the profile based on observed patterns from a normal session (the agent watches for signals and proposes additions when evidence accrues).

`task-agent`/`review-agent`: use when CPU, memory, I/O, database, network, rendering, or cost needs measured bottleneck evidence; skip without a profiling need.

Selects, configures, deploys, verifies, debugs, or tears down a VSS profile (base, search, lvs, warehouse, edge) for NVIDIA's video search and summarization stack.

Set up GPU profiling, tracing, and monitoring for inference workloads using vLLM, SGLang, PyTorch, and dstack services via the Graphsignal Profiler sidecar.

针对 Modular RAG MCP Server 项目的模拟技术面试 Agent。读取用户简历（可选），围绕三个方向进行最多 3 轮深度追问，结束后生成并持久化面试报告（含参考答案、包装识别点评、评分）。Use when user says '模拟面试', '面试练习', '帮我面试', 'mock interview', 'interview practice', '面试', '考我', '开始面试', or wants to practice interviewing about this project.

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

Configure Fish shell abbreviations, completions, and prompt themes easily. Use when setting aliases, writing functions, customizing prompts, or adding plugins.

Guides the user through configuring pi — provider, model, base URL, and API key. Use when the user asks to "setup pi", "configure pi", "pi setup", "set up pi provider", "pi config", "change pi model", or invokes /pi:setup. Only run this skill when the user explicitly requests pi setup — never auto-invoke.

Profile an unfamiliar dataset — shape, grain, quality, nulls, distributions, and duplicates — before any analysis is trusted.