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概要と使いどころ
Personal AI agent visual diary. Auto-records all agent activity, generates daily narrative summaries, visual timeline replay, and AI first-person journal. Use /diary for today's summary, /diary:thoughts for AI personal journal, /diary:replay for visual timeline, /diary:stats for analytics, /diary:persona to view/edit AI personality.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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。
Analyze any codebase's source code in depth and produce structured analysis documents saved as markdown files. Use this skill whenever the user asks to understand how a codebase works — architecture, module design, call flows, data models, design patterns, performance characteristics, or any implementation detail. Trigger on phrases like "analyze the source", "explain this code", "how does X work", "where is Y implemented", "trace the flow of", "what happens when", "read through the code", "code walkthrough", "源码分析", "代码解读", "实现原理", "架构分析", "调用链路", "模块分析", or any code-exploration request. Works with any programming language: TypeScript/JavaScript, Java, Python, Go, Rust, C/C++, and more. Even if the user's question seems simple (e.g., "这个文件是干什么的"), use this skill — a thorough, source-backed analysis document is always more valuable than a surface-level guess.
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。
Builds Quarterly Business Review decks for active clients. Pulls metrics, generates structured QBR with wins, challenges, roadmap, and recommendations. Uses crm-writer to read client data.
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。
Cross-channel campaign performance analysis with blended CAC and budget recommendations
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。
Turns client wins into structured case studies in multiple formats. Gathers before/after metrics, structures as Problem-Solution-Results, and outputs landing page copy, one-pager, social snippets, and email insert.
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。
Analyze conversion funnel drop-offs and identify biggest leak points with impact-ranked recommendations
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。
Analyze A/B test results for statistical significance with ship, extend, or kill recommendations
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 formatted video scripts from transcripts, outlines, or topics with visual and audio columns
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。
Multi-touch attribution analysis across marketing channels with multiple models
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。
Transform raw transcripts, notes, or topics into polished long-form articles in the founder's voice
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。
Rigorous benchmarking of multi-agent coordination systems: experiment design, statistical analysis, human evaluation protocols, and reproducible reporting. NOT FOR ML model evaluation (use llm-evaluation-harness), A/B testing for web products, survey design, or general data science.
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 face recognition systems with InsightFace, ArcFace, enrollment pipelines, HDBSCAN clustering, and privacy-compliant architecture. Activate on: face recognition, face enrollment, face clustering, identity verification, facial search. NOT for: general object detection (computer-vision-pipeline), emotion analysis (ai-engineer).
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。
Interpret and design bounded FIPA communicative-act exchanges using XC00037H semantics while keeping delivery, authority, and external effects separate. NOT for proving delivery, task authorization, or external effect completion.
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 dashboards for migrations and runtimes. Use for authority drift, verifier status, burn-down, runtime health, or pain panels. NOT for vanity analytics, ad hoc charts, or duplicate reporting.
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。
Star schema, snowflake schema, SCD types, and Kimball methodology for analytical data modeling. Activate on: dimensional model, star schema, snowflake schema, SCD, fact table, dimension table, Kimball, grain, surrogate key. NOT for: dbt implementation (use dbt-analytics-engineer), warehouse tuning (use data-warehouse-optimizer).
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。
Master of text-based visual communication using ASCII art, Unicode box-drawing, and structured diagram notation. Creates clear, maintainable diagrams for systems, processes, hierarchies, relationships, and psychological structures. Proactively generates diagrams to enhance understanding. Activate on visualization needs, system architecture, process flows, psychological mapping, or when complex concepts would benefit from visual representation. NOT for photo editing, vector graphics, or GUI-based design tools.
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。
Designs and audits data retention and file compaction for an embedded SQLite datastore in a long-lived service — a unified retention registry (one declared policy per table), TTL / absolute-age / row-count-cap policies, a fail-loud coverage guard, WAL/checkpoint tuning, and auto_vacuum/incremental-vacuum so pruning actually shrinks the file. Use when a SQLite DB grows unbounded, a table has an index but no DELETE, a pruned DB never shrinks on disk, metrics are stored as raw events forever, or a new table needs bounding. Keywords retention policy, TTL, reaper, prune, VACUUM, auto_vacuum, incremental_vacuum, WAL checkpoint, freelist, DB bloat, row cap, per-tenant quota. NOT for Postgres/MySQL/server-DB partitioning or TTL, log-line rate-limiting/sampling, backup/replication, schema migrations, or query-performance indexing.
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。
Digital equity and trauma-informed design for marginalized populations. Activate on "accessibility", "offline-first", "trauma-informed", "reentry", "recovery population", "shared device", "unstable phone", "digital equity", "design justice", "low-literacy", "intermittent access". NOT for general UX, marketing optimization, or enterprise SaaS design.
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。
Meta-skill that orchestrates the discourse skill suite: routes between steel-man-argument, socratic-questioning, toulmin-argument-analysis, logical-fallacy-detector, bad-faith-rhetoric-detector, discourse-elision-analyzer, forensic-speech-structure, and productive-discourse-facilitator. Use when analyzing conversations, facilitating discourse, or operating as a dialogue copilot. Maintains mode (silent analysis, coaching overlay, active facilitator) and decides which skills to invoke based on conversation dynamics.
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。
Implementing distributed tracing with W3C Trace Context — the byte-precise `traceparent` and `tracestate` header formats, OpenTelemetry's W3CTraceContextPropagator as the modern default (replacing X-B3-* and X-Datadog-*), head vs tail sampling, and HTTP→SQL trace propagation via sqlcommenter. Grounded in the W3C REC and OpenTelemetry specs. NOT for OTel metrics/logs pipelines, vendor backend setup (Datadog/Honeycomb/Jaeger/Tempo), or browser RUM tracing.
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。
Builds comprehensive design systems and design bibles with production-ready CSS. Expert in design tokens, component libraries, CSS architecture. Use for design system creation, token architecture, component documentation, style guide generation. Activate on "design system", "design tokens", "CSS architecture", "component library", "style guide", "design bible". NOT for typography deep-dives (use typography-expert), color theory mathematics (use color-theory-palette-harmony-expert), brand identity strategy (use web-design-expert), or actual UI implementation (use web-design-expert or native-app-designer).
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。
Aesthetic assessment and design scoring across 6 dimensions. Use for UI critique, design review, visual quality assessment, remix suggestions. Activate on "design critique", "aesthetic review", "UI assessment", "visual quality", "design score", "remix this design". NOT for implementation (use frontend-developer), accessibility-only audits (use color-contrast-auditor), or brand identity creation.
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。
Great Expectations, dbt tests, anomaly detection, and data contracts for data quality. Activate on: data quality, data validation, Great Expectations, data contract, anomaly detection, SLA, freshness check, schema validation. NOT for: dbt model structure (use dbt-analytics-engineer), schema evolution (use schema-evolution-manager).
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。