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概要と使いどころ
Explore open-source GitHub repository source trees via web browsing to analyze and compare feature implementations at the code level. Supports two modes: cross-project comparison and single-project deep dive. Use when evaluating how OSS projects implement a specific feature, choosing architecture patterns, or benchmarking implementation strategies.
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Format and publish rich Notion documents with structured sections, code blocks, tables, callouts, quotes, mermaid diagrams, and emojis. Use when the user asks to organize, write, or save content to Notion (e.g., "notion에 정리해줘", "notion에 저장해줘"), or when invoked with /notion-format. Detects content type (tech-doc, meeting-notes, analysis, tutorial, bug-report) and applies the appropriate formatting template automatically.
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。
Specialized GitHub PR intelligence agent for automatically gathering comprehensive context from Pull Requests. Activate when users need CI failure analysis, review comment investigation, or PR status assessment. Triggers on requests like "CI 실패 원인 찾아줘", "gather review comments", "check PR status", "analyze 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。
GitHub Pull Request creation specialist. Analyzes user requirements to create PRs with structured titles and bodies matching the user's query language. Handles git change analysis, PR draft creation, user confirmation, and final PR creation via gh CLI.
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。
Structured step-by-step problem decomposition and iterative analysis; explicit request only, never for regular coding tasks, and at most once per task.
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 shares a Sentry URL, says "check Sentry", or wants to investigate production errors. Uses Sentry MCP tools for deep analysis.
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 constructing base / upside / downside scenarios — three-statement modeling, sensitivity analysis, optionality reasoning. Triggers on 'model the scenarios', 'what if growth halves'.
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Use when a bug has multiple plausible causes across layers — competing hypotheses, validation loops, evidence-based conclusions — even when the user just says 'why is this happening?'.
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 packaging a codebase to a single AI-friendly file for LLM analysis — local or remote, XML/Markdown/JSON, token counting, gitignore filtering, peer-side `repomix` CLI.
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 sequencing market entry — geo / segment / vertical, beachhead selection, regulatory-delta. Triggers on 'should we enter market X', 'which segment first'.
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Use when diagnosing where a SaaS or product funnel leaks — visitor → signup → activation → paid → retained — channel-agnostic, conversion-rate-driven.
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 analysis of articles/long-form via thinking frameworks (SCQA, mental models, inversion) — 'analyze article', 'deep dive', 'extract insights', URL/text wanting depth not summary.
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 mapping competitors, naming defensibility, and finding white-space — moat reasoning, where-to-play, where-not-to-play. Triggers on 'who are we competing with', 'what's our moat'.
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 multi-step investigation — deep research carried end-to-end without per-step approval; explicit request only, never for normal feature work.
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 shares a Sentry error, Jira bug ticket, or error description and wants root cause analysis. Also for proactive bug hunting and code audits for hidden bugs.
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 deciding insource vs outsource vs acquire — integration-cost analysis, dependency-risk, optionality preservation. Triggers on 'should we build', 'buy vs partner'.
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 a two-agent independent review/redteam followed by peer collaboration to produce a consensus superset of findings and enumerated revision requests. Use when Codex 5.5 and Claude Opus 4.7 should first critique a matter independently, then exchange work, synthesize the best combined analysis, and finish with a single agreed revision list.
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。
Analisa seu histórico recente de chats do Claude Code para identificar padrões de codificação, lacunas no desenvolvimento e áreas para melhoria, seleciona recursos de aprendizagem relevantes do HackerNews e envia automaticamente um relatório de crescimento personalizado para suas DMs do Slack.
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。
Fornece orientação para pesquisa de interpretabilidade mecanística usando TransformerLens para inspecionar e manipular internals de transformers via HookPoints e caching de ativações. Use ao fazer engenharia reversa de algoritmos de modelos, estudar padrões de atenção ou realizar experimentos de activation patching.
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。
Fetch transcripts from YouTube videos for summarization, analysis, or reference. Accepts video ID or full URL. No API key required. Triggers: YouTube transcript, video transcript, get subtitles, what did they say in the video, summarize YouTube, extract video text, caption from video.
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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy. Triggers: create a skill, new skill, build a skill, skill creation, write a SKILL.md, evaluate skill, test skill, skill eval, benchmark skill, optimize skill description.
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 & Tools] Use when you need to apply structured, reflective problem-solving for complex tasks requiring multi-step analysis, revision capability, and hypothesis verification.
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[Quality] Use when you need to research and configure code quality tooling for any tech stack — linters, formatters, static analysis, pre-commit hooks, and CI gates.
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] Use when you need to analyze market landscape: competitors, sizing (TAM/SAM/SOM), trends, SWOT, customer segments.
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。