6,815 件 ・ 関連度順
概要と使いどころ
Performance measurement, attribution modeling, and marketing ROI analysis. Use when setting up tracking, analyzing campaign performance, building attribution models, or creating marketing reports.
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。
Verification loop for Spring Boot projects: build, static analysis, tests with coverage, security scans, and diff review before release or PR.
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。
Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.
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。
Nuxt 4 应用模式，涵盖水合安全、性能优化、路由规则、懒加载，以及使用 useFetch 和 useAsyncData 进行 SSR 安全的数据获取。
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。
Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization. Transforms vague video ideas into detailed scene-by-scene plans (scenes.md). Conducts research, asks clarifying questions about audience/scope/focus, and outputs comprehensive scene specifications ready for implementation with ManimCE or ManimGL. Use this BEFORE writing any Manim code. This skill plans the video; use manimce-best-practices or manimgl-best-practices for implementation.
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。
Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
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。
Modern .NET project structure including .slnx solution format, Directory.Build.props, central package management, SourceLink, version management with RELEASE_NOTES.md, and SDK pinning with global.json.
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。
[AUTO-INVOKE] MUST be invoked when debugging failed on-chain transactions. Covers transaction receipt analysis, gas diagnosis, calldata decoding, revert reason extraction, and state verification. Trigger: any task involving failed tx analysis, revert debugging, or on-chain transaction troubleshooting.
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。
Workflow for publishing skills and agents to the dotnet-skills Claude Code marketplace. Covers adding new content, updating plugin.json, validation, and release tagging.
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。
Persist AI chat conversations to Neon Postgres with full support for AI SDK message parts including tools, reasoning, and streaming. Uses UUID v7 for chronologically-sortable IDs.
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。
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
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 agent workflow patterns including ReAct agents, multi-agent systems, loop control, tool orchestration, and autonomous agent architectures. Use when building AI agents, implementing workflows, creating autonomous systems, or when user mentions agents, workflows, ReAct, multi-step reasoning, loop control, agent orchestration, or autonomous AI.
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。
Guidance for selecting appropriate AI model (sonnet vs haiku) based on task complexity, reasoning requirements, and performance needs. Use when implementing agents or justifying model selection.
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。
Create, refine, and manage issues. Use for creating new issues from loose ideas, refining ambiguous issues, bulk operations, or JSON export.
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。
Expert prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reliability, efficiency, and measurable outcomes.
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。
Design and implement evaluation frameworks for AI agents. Use when testing agent reasoning quality, building graders, doing error analysis, or establishing regression protection. Framework-agnostic concepts that apply to any SDK.
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。
[00] TnR ABSOLUTE RIGOR — Systemic Verification Doctrine. Forced cognitive exertion for high-stakes investigations. Mandates absolute deconstruction, mathematical proof chains, and ≥95% derived certainty. Zero-tolerance for heuristics or sentiment-based reasoning. Shortcuts are defined as intentional hallucinations.
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。
Guide for authoring specialized AI agents. Use when creating, updating, or improving agents, choosing models, defining focus areas, configuring tools, or learning agent best practices.
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。
Earnings analysis — pre- and post-earnings. Pre-earnings preview: prior-guidance review, recent-events tracking, last call's Q&A, and a key-things-to-watch framework for an upcoming release. Post-earnings: two tiers — a fast in-chat summary card (default) and a full Markdown research report (on request). Covers beat/miss, segments, margins, guidance, estimates, valuation. US / HK / A-share. Use whenever the user wants an earnings preview or a post-earnings / quarterly-results writeup. Triggers: "earnings update", "quarterly results", "Q1/Q2/Q3/Q4 results", "earnings report", "post-earnings analysis", "beat/miss", "guidance update", "earnings preview", "pre-earnings", "what to watch this earnings", "before earnings", "财报分析", "业绩更新", "季度业绩", "季报", "年报", "盈利分析", "财报点评", "财报前瞻", "业绩前瞻", "财报预览", "上季度指引", "財報分析", "業績更新", "季度業績", "季報", "年報", "財報點評", "財報前瞻", "業績前瞻", "財報預覽".
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。
ADI-cycle structured reasoning (Abduction-Deduction-Induction-Audit-Decide). Use for complex decisions when multiple hypotheses need to be considered.
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。
Use when verifying information (fact, number, quote, event, statement) against authoritative primary sources, or cross-checking a number via one-level metric decomposition (Z = P × Q). Triggers: "verify X", "is this true", "find the original source", "where is this number from", "two sources disagree", "is it true X never did Y". Covers five scenarios: (1) basic truthfulness check, (2) completeness / out-of-context quoting, (3) one-level reasoning verification, (4) negative-statement handling, (5) multi-source conflict side-by-side output. Dig into whitelisted primary sources only (user-supplied files, official websites & databases, authoritative industry sources); cited reports / charts / datasets must be downloaded and read locally to count as verified — if download is blocked, hand the link to the user. If nothing can be found, plainly state "cannot verify" rather than guessing, patching, or citing secondary paraphrases. Always reply in the user's question language.
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 a topic-focused briefing in HTML from public news sources. Use when user asks for a briefing / observation / digest / 简报 / 观察 on any subject — region (Middle East, ASEAN, India), industry (semiconductors, EV supply chain, AI), policy issue (AI regulation, critical minerals, cross-border payments), institution (Fed, ECB, IMF), or theme. Output is a single self-contained HTML file with blue-color "TOPIC BRIEF" branding, optimized for both browser viewing and direct copy-paste into 微信公众号 / WeChat Official Account editor. Walks through 5 steps with one user confirmation midway. Do NOT use this skill for short summaries (<1000 字), single-piece news commentary, or already-defined report templates.
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。
Start, continue, keep, pause, copy, watch and stop authorised Anabasis v2 campaigns through `bun run runs`: launch a campaign under a name, go on with one from its log on another login or commit, keep one going across logins until it ends on its own terms, pause one at a clean point, copy a stopped one to another worktree, read each run's status and each login's room, reach the other hosts, and stop one and release what it held. Use when the operator asks to start, launch, resume, continue, move, keep, pause, copy or stop a campaign or a run, which logins have room, how the runs stand on any host, whether a campaign is ready for its next move, or why a move was refused. Owns the run's life on the host; run-improvement-campaign reads the table, and whole-run-investigation reads what a run did.
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。
The harnesses a campaign keeps, read outside a run: which there are and where each came from, what each is made of and what moved from its parent, what each was measured to be, trying one on a task, the audit before a promotion and the blind review at a handover, whether a part earns its place, and changing what makes a harness or what a seat is told about one. Use when the operator asks which harness is current, what a Builder changed, whether a harness is ready to promote or hand over, to run a kept harness on a task, or to change the harness contract. Reading one run is whole-run-investigation's, wording a claim attribution-and-proof's.
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。