编码规范、框架、重构、代码审查（1.7万 个）
Type-safe URL query state management with nuqs 2.x. Use when writing or reviewing code that uses useQueryState, useQueryStates, URL search params, query parameters, nuqs parsers, createLoader, createSearchParamsCache, createSerializer, or URL state in Next.js, React, Remix, React Router, or TanStack Router.
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Score a PhD applicant's profile and rank candidate advisors using a connection-first 4.0-scale scoring system. Best-supported for physics / HEP and materials science (MSE), with the scoring engine extensible to chemistry, biology, CS, math, EE, ChemE, earth science (each with field-specific caveats — see references/journal_tiers.md). Use when the user wants to evaluate their PhD application chances, find matching advisors at top US programs, score a CV for graduate school, or compare candidate professors. Also triggers when the user mentions phdtaketaketake or its connection-first philosophy of valuing advisor network over h-index.
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Secure environment variable management with Varlock. Use when handling secrets, API keys, credentials, or any sensitive configuration. Ensures secrets are never exposed in terminals, logs, traces, or Claude's context. Trigger phrases include "environment variables", "secrets", ".env", "API key", "credentials", "sensitive", "Varlock".
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Use when the user wants to create, configure, scale, debug, observe, or roll out container workloads on DataRobot's Workload API. Triggers: deploy a container as a managed service; list/start/stop workloads; change replica counts or autoscaling; pick CPU/GPU compute bundles; inject DataRobot credentials as env vars; diagnose stuck/errored/crash-looping workloads (CrashLoopBackOff, ImagePullBackOff, OOMKilled, probe failures, exec format error); pull application logs/OpenTelemetry traces/metrics/request stats; create or iterate container artifacts; build images server-side; lock artifacts for production; zero-downtime rolling artifact replacement.
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Refactor large DataRobot skill files by moving detailed content into directly linked reference files while preserving meaning. Use when a skill triggers context-window warnings, needs progressive disclosure, or should be chunked without changing guidance.
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执行msProbe数据比对并分析比对结果，定位确定性计算问题首个输入一致输出不一致的API。
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当用户提供 GitHub 文件页面链接，或希望读取某个仓库中的源码、配置、README、Markdown、docs 内容时，使用此技能。技能支持将 `github.com/<owner>/<repo>/blob/<ref>/...` 转换为 `raw.githubusercontent.com` 链接并获取内容；读取仓库 docs 时先列出仓库根目录、按真实结构定位 `docs/` 目录（语言子目录、索引），不要假设所有仓库都有固定目录或 `agent_router.md`（该文件仅当根目录确实存在时才可选参考）。
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Install and verify the msmodeling development environment. Use when the user explicitly asks to install msmodeling dependencies, set up this repository, create `myenv` with `uv`, install this repository's `requirements.txt`, set project `PYTHONPATH`, or configure `HF_ENDPOINT`; if the user only says to install an environment, ask whether they mean msmodeling dependencies before proceeding.
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解析中文自然语言中的 AISBench 测评需求，检查 Python 与 AISBench 运行环境，通过分轮追问确认关键配置，将基准名称映射为仓库内的数据集任务，在用户最终确认后生成并执行 AISBench CLI，并返回精度指标和产物路径。适用于用户要求使用 AISBench 评测模型或运行数据集；不适用于实现新数据集或仅解释基准概念。
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MindStudio Profiler Analyze（msprof-analyze）是面向 AI 训练与推理场景的性能分析工具，基于采集得到的 profiling 数据进行统计、比对和诊断，帮助定位计算、通信、调度及集群场景下的性能瓶颈。
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对 msMemScope 显存数据做全链路处理：根据用户的显存问题诉求（OOM、显存泄漏、显存占比拆解、Step 间对比等），指导并帮助用户以最合适的 msMemScope 采集配置完成显存数据采集（支持命令行、Python 接口、mstx 打点三种采集方式，覆盖训练、推理 vLLM-Ascend、FSDP、强化学习 verl 等场景）；对已采集的 memscope_dump_*.csv/db 数据做系统性解读与问题诊断（整体显存曲线趋势分析、显存使用大头按模块/组件拆解分析、显存峰值点各模块与流程占比分析，以及对显存泄漏、OOM 等典型问题的根因定位与原因分析）。
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昇腾AscendC算子调试工具（msDebug）技能，含两大流程：①上板调试——算子加 -g -O0 编译后由 msdebug 拉起，支持断点、单步、变量/内存打印、核切换、寄存器读取；②coredump解析——用户指定 core 文件路径后，msdebug 加载解析挂掉代码行/异常调用栈/现场变量。触发关键词：msdebug、算子调试、上板调试、断点、单步调试、打印变量、读内存、核切换、寄存器、coredump、core文件、调用栈、崩溃解析
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在遇到模型精度问题，需要分析定位时使用。典型的精度问题包括回复输出中有乱码或重复、精度测评不达标等。
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Build AI champion programs for adoption. TRIGGERS - Use when user needs help with ai-champion-program related tasks.
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Design AI-powered code review systems. TRIGGERS - Use when user needs help with ai-code-review-system related tasks.
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Build AI code generation systems. TRIGGERS - Use when user needs help with ai-code-generator related tasks.
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Design AI API gateways with rate limiting and routing. TRIGGERS - Use when user needs help with ai-api-gateway related tasks.
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Design after-school program activities and structure. TRIGGERS - Use when user needs help with after-school-program related tasks.
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Design activity programs for senior engagement. TRIGGERS - Use when user needs help with activity-program-senior related tasks.
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Design accessibility training. TRIGGERS - Use when user needs help with accessibility-training-program related tasks.
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kbo-cli 새 버전을 릴리즈한다. develop 에서 package.json 버전을 올리고 커밋·태그를 만든 뒤, main 을 develop 으로 fast-forward 동기화해 origin 으로 push 하면, GitHub Actions 가 npm 배포와 GitHub Release 생성을 처리한다. 인자 형식 — `/release` (patch), `/release minor`, `/release major`, `/release 1.2.3` (명시 버전).
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Lightweight refactor: audit → plan → approve → implement in a single Opus context, no sub-agent fan-out. Behavior preservation is the goal — verifies tests still pass, optionally commits, and offers a separate /code-review pass at the end. Use by default; reach for /refactor only when the cleanup needs parallel fan-out or exceeds one context.
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Lightweight refactor: audit → plan → approve → implement in a single Opus context, no sub-agent fan-out. Behavior preservation is the goal — verifies tests still pass, optionally commits, and offers a separate /code-review pass at the end. Use by default; reach for /claude-setup:refactor only when the cleanup needs parallel fan-out or exceeds one context.
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Refactoring pipeline: analyzes a target file or directory for code quality issues, plans safe incremental improvements, optionally writes tests first as a safety net, implements the changes, and reviews the result. Orchestrates refactor-planner → (test-writer) → parallel-task-orchestrator → code-reviewer.
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