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Analyze an organization's sub-transaction patterns in TRES Finance, identify groups of repetitive transactions, and propose data-driven rollup rules that consolidate them into one aggregated entry per interval (daily or monthly) for cleaner ERP integration. Also lists and deletes rollup rules. Trigger this skill whenever the user asks about rollup rules, transaction aggregation, consolidating transactions, reducing transaction noise, rolling up gas fees, rolling up staking rewards, rolling up micro-transactions, or collapsing many small ledger entries into fewer summary entries. Also trigger on "create a rollup rule", "suggest rollup rules", "what should I roll up", "show my rollup rules", "delete a rollup rule", "aggregate transactions", "too many transactions", "reduce transaction count", "roll up fees", "daily rollup", "monthly rollup". If a wallet has too many transactions, high-frequency activity, or noisy ledger entries, proactively suggest rollup rules. For computing the EXACT impact of a single already-specified rule or reviewing submitted/pending rules, use the tres-rollup-review skill instead.

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This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.

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 parallel subagents for large-scale paper screening and deep dive 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。

Generate academic referee reports for economics/finance papers, followed by a 150-word letter to the editor with recommendation (Reject / Major Revision) and Kai Wu signature. Two modes (normal / high-level), configurable number of comments; recommendation choice drives evaluation tone (Reject → negative, Major Revision → neutral). Trigger when user says "referee report" / "write referee report" / "审稿报告" / "写审稿意见" / "generate referee report" / "review this paper".

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。

Collaboratively build and refine paper screening rubrics through brainstorming, test-driven development, and iterative feedback

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Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.

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 strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints. Output: optimized detailed outline ready for systematic writing (use with academic-paper-composer skill).

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Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

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Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.

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AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

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Discard all frames currently held by the Editor Profiler (UnityEditorInternal.ProfilerDriver.ClearAllFrames). Cannot be undone.

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Coordinate Lark/Feishu CLI tasks from Codex. Use when a request involves Feishu/Lark docs, wiki, Drive files, Sheets, Base, Calendar, Minutes, IM, Mail, Tasks, Contacts, Slides, whiteboards, approvals, attendance, or when a Lark URL/token must be read, edited, summarized, routed, or turned into a real work artifact.

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Review a git diff or explicit file scope for reuse, code quality, efficiency, clarity, and standards issues, then optionally apply safe Codex-driven fixes. Use when the user asks to "simplify code", "review changed code", "check for code reuse", "review code quality", "review efficiency", "simplify changes", "clean up code", "refactor changes", or "run simplify".

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。

Best practices and example-driven guidance for building SwiftUI views and components, including navigation hierarchies, custom view modifiers, and responsive layouts with stacks and grids. Use when creating or refactoring SwiftUI UI, designing tab architecture with TabView, composing screens with VStack/HStack, managing @State or @Binding, building declarative iOS interfaces, or needing component-specific patterns and examples.

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 executing implementation plans with independent tasks in the current session

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 hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.

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 implementing any feature or bugfix, before writing implementation code

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。

Discover, analyze, and prioritize keywords for SEO and GEO content strategies from a seed keyword or niche. Identifies high-value opportunities based on search volume, competition, intent, and business relevance. Generates topic clusters. For building a dated editorial calendar from your own Search Console data, use `content-planner` instead — this skill is seed-driven keyword discovery, not calendar scheduling. Use when asked to "find keywords", "keyword research", "keyword analysis", "search volume", "keyword difficulty", "content ideas from a seed", or any keyword discovery 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。

Search Experience Optimization (SXO), the bridge between SEO and UX/CRO. Audits the journey from the SERP click to the on-page goal: click-through factors (title, meta, rich results), then post-click signals that keep users and drive conversions: above-the-fold relevance and intent match, page speed / Core Web Vitals, readability, clear CTAs, mobile usability, and what causes pogo-sticking back to Google. Use when the user has decent rankings but poor CTR or poor on-page conversion, wants better dwell time / engagement, less bounce, or a page experience aligned with search intent. Trigger on: "SXO", "search experience optimization", "good rankings but low CTR", "high bounce rate from search", "pogo-sticking", "improve dwell time", "SEO and conversion", "ranking but not converting", "engagement signals", "make this page convert search traffic". For pure landing-page conversion in ads use /google-ads-landing; for content quality use /seo-page.

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。

GSC-driven content calendar. Pulls real Search Console data, finds the highest click-potential opportunities (striking-distance queries at positions 5-20, unanswered query intent, related-keyword expansions), and produces a dated, prioritized content calendar — ready to hand to /content-writer. Use when the user asks "plan my content", "what should I write next", "content calendar", "content plan", "content roadmap", "editorial calendar", "what topics will rank", "find quick-win SEO topics", "click-potential analysis", or "schedule my SEO content".

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。

Hypothesis-driven, tool-grounded security review of coverage gaps

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Drive an engine app headlessly in a pty, record a video of the whole verification, and open a summary page (video + timeline + checks) with pixel open.

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。

From a Tutti checkout, run, audit, freshly replay, publish, or diagnose Session Replay cassettes that are driven by case-repository scenario scripts (CDP), not by interactive UI recording. Use for real-Provider capture while a scenario.mjs executes, cassette transport or semantic-state mismatches, fresh replay qualification, AgentGUI replay evidence, and product-side support for a new Agent Target beyond local:codex / local:claude-code. Do not use to author Case metadata or scenario scripts (case repository write-replay-case), or for executionKind "ui" Cases.

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。