9,744 件 ・ 関連度順
Compatibility skill for analytics tracking. Use when a user or upstream workflow invokes this name; route the task to `analytics` while preserving the requested scope and source-specific intent.
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。
Compatibility skill for competitor alternatives. Use when a user or upstream workflow invokes this name; route the task to `competitors` while preserving the requested scope and source-specific intent.
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。
Compatibility skill for ab test setup. Use when a user or upstream workflow invokes this name; route the task to `ab-testing` while preserving the requested scope and source-specific intent.
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。
Compatibility skill for aso audit. Use when a user or upstream workflow invokes this name; route the task to `aso` while preserving the requested scope and source-specific intent.
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 the user asks to "plan an influencer campaign", "build a campaign blueprint", or "launch a product with creators"; produces campaign objectives, platform and influencer-tier strategy, content requirements, a phased timeline, budget allocation, and KPI targets. Not for writing individual creator briefs — use brief-generator; not for the overall product-launch plan (tiering, calendar, press, community day) — use launch-tier-planner, which hands this skill the creator lane. A launch request that does not mention creators routes to the launch discipline, not here. 达人营销策划/种草方案
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。
Diagnose and draft or explicitly apply paid-ad optimizations using evidence, financial constraints, experiments, and capability-gated adapters. Use for campaign optimization, budget reallocation, bid changes, pausing or archiving ads, requests to delete campaigns, search-term or negative-keyword actions, creative rotation, or improving CPA and ROAS.
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。
Audit paid-ad landing pages for message match, mobile experience, performance, accessibility, trust, forms, consent, tracking, security, and conversion friction. Use for landing-page audit, post-click experience, LP audit, conversion-rate optimization, form optimization, ad-to-page message match, redirects, blocked navigation, or requests involving private, loopback, link-local, or metadata IP destinations.
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 a paid-media client, brand, account, data-source, privacy, and mutation-guardrail profile for Claude Ads. Use for onboarding, initial configuration, brand DNA, API tokens or credential profiles, environment-variable or keychain setup, connecting exports or read adapters, safe native or verified-local installation, curl-pipe-bash install requests, declaring KPIs, or preparing a new advertising 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。
Draft or explicitly apply a paid-ad campaign launch through Claude Ads capability-gated adapters. Use for campaign creation, launch plans, publishing ads, activating campaigns, uploading creative, or requests to push a campaign live.
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。
Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to add or total Meta and Google conversions, incompatible reporting-window aggregation, GA4 attribution, MMP review, AppsFlyer, Adjust, Branch, Singular, or cross-platform discrepancies.
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。
Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).
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。
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.
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。
Autonomous coding agent. Delegate any task that involves understanding, writing, or running code — from a GitHub issue, a bug report, or a user request. It explores, implements, and verifies on its own.
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 the user is unsure which skill to use or where to start. Interviews the user with targeted questions and recommends the best skill(s) from the installed library for their goal.
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。
Helps an AI assistant work with the Miraheze wiki farm — writing wiki requests that get approved, navigating ManageWiki, doing common how-to tasks (templates, skins, permissions, custom domains, backups), writing regex for MediaWiki search-and-replace, AND writing actual article and page content for Miraheze-hosted wikis. Miraheze does NOT ban generative AI; AI-written content is permitted (subject to per-wiki rules). MADE BY SQERSTERS
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。
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.
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。
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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。
GitHub operations using gh CLI for any repository. Use when the user asks to "create pr", "create pull request", "view pr", "check ci", "pr status", "list prs", "create issue", "view issue", "search code", or any other GitHub-related operations. Handles PR creation with proper base branch detection, template support, and project conventions.
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。
Ensure OpenAPI specs define consistent request/response schemas, error model, auth, pagination, and backward compatibility.
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。
Detects mass assignment via create/update($request->all()), unguarded models, and missing authorization on mutating controller actions in Laravel.
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。
Reviews GitHub Actions workflow diffs for script injection of untrusted input, pull_request_target with untrusted checkout, over-broad GITHUB_TOKEN permissions, and unpinned third-party 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。
Develops an implementation plan ready for wave-orchestration to execute. Takes the user's goal or rough plan as input, mines the codebase for facts, grills the user one question at a time for the decisions, drafts the planning/ artifacts (task DAG, wave table, worker prompt template, state file), then reviews its own plan on two axes before seeking approval. Use when the user wants to turn a feature idea, master plan, or backlog into a wave-orchestration execution plan.
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。
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
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。
Build and review evidence tagged Blender architectural candidates, preserve unrelated scene content, and produce requested photographic materials, stills and portable model deliveries.
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。