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概要と使いどころ
Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready evidence. Use when (1) you need TAM, SAM, SOM, whitespace, or category sizing; (2) you must compare competitors, pricing, positioning, or customer segments before acting; (3) the user asks whether a niche, launch, expansion, or go-to-market bet is actually worth pursuing.
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When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' or 'monetization.' This skill covers pricing research, tier structure, and packaging strategy.
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。
Navigate moral reasoning from personal dilemmas to academic philosophy.
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。
Tracks competitors weekly across 6 signals: pricing page diffs, homepage positioning changes, blog/RSS posts, job postings (hiring as strategy signal), GitHub star velocity and releases, and daily critical-change alerts for pricing or funding keywords. Delivers a structured digest to Slack, Telegram, WhatsApp, or Discord every Monday. Fires same-day alerts for critical changes. Use when asked to "add competitor", "track competitor", "competitor digest", "what changed at [company]", "competitor report", "monitor [company]", "who is [company] hiring", "did [company] change pricing".
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。
Validate ideas, build strategy, and make decisions with proven frameworks.
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AEO — Agent 效果运营平台。自动发现 Agent 效果漂移、诊断根因、运行 AI 数据闭环工具链，给出 AI 效果优化方案。Measure agent performance, attribute outcomes, track quality trends, optimize cost, and monitor SLAs.
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Maxim 2D cartoon explainer video — engineered for learning retention and friendly brand affinity. Uses Dual Coding Theory + Cognitive Load Reduction + Ekman Universal Emotion to make complex ideas memorable and brands feel trustworthy-approachable.
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 wiki health — "wiki health check", "audit the wiki", "find contradictions", weekly pass, before a major content release. Catches contradictions, stale pages, orphans, duplicate concepts and broken links.
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Generate logo directions — "give me logo concepts for", "logo ideas for", "design a logo for". Emits 3 to 5 distinct directions as real editable SVG vector code, not raster mockups.
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。
Qualify an inbound lead — "is this lead worth my time", "qualify this lead", "should I take this client". Applies MEDDIC and SPIN scoring and returns a verdict with reasoning.
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。
Review and verify unverified wiki pages — "review unverified pages", "verify wiki content", verification pass, after a major ingest cycle, before content release. The gate that turns AI-generated knowledge into trusted knowledge.
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。
Ingest raw sources into the structured wiki — "ingest", "add this to my wiki", new files in raw/, clippings, sources, ideas, nightly ingest. Produces pages with YAML frontmatter and a mandatory Counter-Arguments section.
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。
Structure AI work artifacts under .aiwork/{YYYY-MM-DD}_{slug}/ folders using the project's protocol (intent, triage, research, spec, prd, areas, plan, review, notes, docs/). Use when the user asks to plan, capture an intent, make a spec, triage, research a task, write a report, code review, summarize findings, save the work, document decisions, record this, write that down, persist findings, or references any path under .aiwork/. Also use when starting a non-trivial task that needs a plan or spec before implementation, or when finishing one and capturing notes.
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。
Visual whiteboard collaboration for Copilot CLI. Creates an interactive whiteboard that opens in your browser — draw, sketch, add sticky notes, then share everything back with Copilot. Copilot sees your drawings and text, and responds with analysis, suggestions, and ideas.
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。
Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.
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。
Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.
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 CLI (gh) comprehensive reference for repositories, issues, pull requests, Actions, projects, releases, gists, codespaces, organizations, extensions, and all GitHub operations from the command line.
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。
Migration and code evolution instructions generator for GitHub Copilot. Analyzes differences between two project versions (branches, commits, or releases) to create precise instructions allowing Copilot to maintain consistency during technology migrations, major refactoring, or framework version upgrades.
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 you need to check feature flag states, compare channels, or debug why a feature behaves differently across release channels.
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。
When user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.
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。
Comprehensive skill for working with Azure DevOps REST API across all services including Boards (work items, queries, backlogs), Repos (Git, pull requests, commits), Pipelines (builds, releases, deployments), Test Plans, Artifacts, organizations, projects, security, extensions, and more. Use when implementing Azure DevOps integrations, automating DevOps workflows, or building applications that interact with Azure DevOps services.
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。
Serves as a reviewer of the codebase with instructions on looking for Apple App Store optimizations or rejection reasons.
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。
Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
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。
Triage and resolve Arch Linux issues with pacman, systemd, and rolling-release 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。