3,340 件 ・ 関連度順
概要と使いどころ
Analyze project and generate or enhance build automation file (Makefile, Taskfile.yml, Justfile, Magefile.go). If a build file already exists, improves it by adding missing targets and best practices. Use when user says "generate makefile", "create taskfile", "add justfile", "setup mage", or "build automation".
日本語の概要は準備中です。原文の説明を表示しています。
Set up agent context for a project. Analyzes tech stack, installs relevant skills from skills.sh, generates custom skills, and configures MCP servers. Use when starting new project, setting up AI context, or asking "set up project", "configure AI", "what skills do I need".
日本語の概要は準備中です。原文の説明を表示しています。
Analyze project and generate Docker configuration: Dockerfile (multi-stage dev/prod), compose.yml, compose.override.yml (dev), compose.production.yml (hardened), and .dockerignore. Includes production security audit. Use when user says "dockerize", "add docker", "docker compose", "containerize", or "setup docker".
日本語の概要は準備中です。原文の説明を表示しています。
Self-improve AI Factory skills based on project context, accumulated patches, and codebase patterns. Analyzes what went wrong, what works, and enhances skills to prevent future issues. Use when you want to make AI smarter for your project.
日本語の概要は準備中です。原文の説明を表示しています。
Refine an existing implementation plan with a second iteration. Re-analyzes the codebase for gaps, missing tasks, and wrong dependencies. Use after $aif-plan or to improve an $aif-fix plan. Optional +check flag validates refinements via a fresh-context subagent.
日本語の概要は準備中です。原文の説明を表示しています。
Generate architecture guidelines for the project. Analyzes tech stack from DESCRIPTION.md, recommends an architecture pattern, and creates .ai-factory/ARCHITECTURE.md. Use when setting up project architecture, asking "which architecture", or after $aif setup.
日本語の概要は準備中です。原文の説明を表示しています。
Refine an existing implementation plan with a second iteration. Re-analyzes the codebase for gaps, missing tasks, and wrong dependencies. Use after /aif-plan or to improve an /aif-fix plan. Optional +check flag validates refinements via a fresh-context subagent.
日本語の概要は準備中です。原文の説明を表示しています。
QA workflow for testing a feature or task implementation. Analyzes changes, produces test plans, and describes concrete test scenarios. Use when user says "test this", "write test plan", "what should I test", or "QA this branch".
日本語の概要は準備中です。原文の説明を表示しています。
Generate architecture guidelines for the project. Analyzes tech stack from DESCRIPTION.md, recommends an architecture pattern, and creates .ai-factory/ARCHITECTURE.md. Use when setting up project architecture, asking "which architecture", or after /aif setup.
日本語の概要は準備中です。原文の説明を表示しています。
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective".
日本語の概要は準備中です。原文の説明を表示しています。
Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when asked to "review this PR", "code review", "pre-landing review", or "check my diff".
日本語の概要は準備中です。原文の説明を表示しています。
Systematic debugging with root cause investigation. Four phases: investigate, analyze, hypothesize, implement. Iron Law: no fixes without root cause.
日本語の概要は準備中です。原文の説明を表示しています。
运行程序采集 Profiling 数据，再用 msprof-analyze 分析TFLOPS 与 MFU。
日本語の概要は準備中です。原文の説明を表示しています。
Analyze Ascend NPU schedule, operator dispatch, operator launch, and Host Bound profiling issues in Ascend profiling data. Use when need to diagnose device Free time, framework/operator dispatch latency, launch latency, PYTORCH_API/CANN_API launch gaps, aclrtSynchronizeStream stalls, task queue behavior, CPU scheduling interference, GC/lock pauses, CPU affinity, or schedule-side optimization actions.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze Ascend NPU computation-side profiling data for single-card runs or a selected rank from multi-card runs. Use this skill when the user asks to diagnose computation bottlenecks, AI Core / AI Vector / AICPU hotspots, dynamic shape overhead, block dim issues, redundant TransData/Transpose/Cast, cross-stream waits, frequency/runtime-state issues, or fusion opportunities.
日本語の概要は準備中です。原文の説明を表示しています。
分析 msProbe compare 精度比对结果文件（CSV/XLSX），定位整网精度问题与数值差异。支持统计量模式，输出分析报告。支持辅助信息协助定位：辅助信息（历史结论/已知根因/已排除算子/嫌疑区域等）建议在请求中附带（不依赖交互工具）。若请求中未附带且运行环境无 AskUserQuestion，则跳过辅助信息收集、照常完成分析，报告中省略辅助信息章节并注明原因。
日本語の概要は準備中です。原文の説明を表示しています。
Ascend cluster comparison tool. Invoke when user asks to compare two cluster datasets (DB or TEXT), or to generate cluster_analysis_output from raw profiling data via msprof-analyze and then compare.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze Ascend NPU collective communication profiling data with a DB-first workflow. Use when the user provides `cluster_analysis_output/cluster_analysis.db`, rank-level `analysis.db`, rank-level `ascend_pytorch_profiler_{rank_id}.db`, together with `profiler_info.json`, and asks about HCCL or hcom communication cost, collective communication TOP ops, wait time, slow rank/straggler, Notify Wait, bandwidth, retry, relay, SDMA/RDMA/HCCS links, communication matrix, or Ascend communication fault patterns.
日本語の概要は準備中です。原文の説明を表示しています。
分析 PyTorch memory snapshot pickle 文件（_dump_snapshot 导出的内存快照），提供内存峰值、碎片、泄漏、OOM 检测与交互式 HTML 报告。仅当用户明确提及 memory snapshot、内存快照、_dump_snapshot、pickle 内存文件 或需要对 snapshot pickle 做内存分析时才触发，不处理一般的 NPU 性能分析、SQLite 查询或通用内存问题。
日本語の概要は準備中です。原文の説明を表示しています。
AI Trading Analyst for Hermes — full stock analysis with 5 parallel subagents, investment thesis, technical/fundamental/sentiment/risk analysis, options strategies, portfolio review, stock screener, and PDF reports. Say "trade analyze AAPL", "trade quick NVDA", "trade screen growth", etc.
日本語の概要は準備中です。原文の説明を表示しています。
Sector Rotation & Analysis — analyzes sector momentum rankings across all 11 GICS sectors, money flows, economic cycle positioning, relative strength, top stocks per sector, valuations, and rotation signals. Triggered by "trade sector <sector>" or "trade sector rotation".
日本語の概要は準備中です。原文の説明を表示しています。
Deep-dive ONE competitor's organic footprint — exact ranking keywords and URLs, content themes, backlink profile, and exploitable gaps — with findings written into brand/competitors.md. Use this skill when the user names a competitor and wants to know what to learn from them, counter, or outrank, including head-to-head comparisons against the user's own domain. For market-level mapping first, use openseo-competitive-landscape. Triggers: "analyze competitor", "competitor keywords", "competitor backlinks", "beat <competitor>", "competitor seo teardown".
日本語の概要は準備中です。原文の説明を表示しています。
Research and analyze competitors to find positioning gaps and strategic opportunities. Use this skill whenever the user mentions competitors, competitive analysis, competitor teardown, market landscape, 'who else does this', 'how are we different', or competitor research. Also trigger when the user is entering a new market, when positioning feels weak or generic, when preparing for a launch, when any downstream skill needs competitors.md but it doesn't exist, or when the user asks about differentiation or market gaps. Even if the user just names a competitor casually ('what does X do?'), this skill likely applies. Three modes: Quick Scan, Deep Teardown, Gap Finder.
日本語の概要は準備中です。原文の説明を表示しています。
디자인 레퍼런스 분석 에이전트. 디자인 레퍼런스/ 폴더의 PDF, JPG, PPTX 파일을 분석하여 컬러 팔레트, 레이아웃 패턴, 도식 스타일, 분위기 리듬을 추출합니다. 출력: design_analysis.md. 트리거: 디자인 분석, 레퍼런스 분석, design analysis, 디자인 레퍼런스
日本語の概要は準備中です。原文の説明を表示しています。