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概要と使いどころ
AionUi WebUI configuration expert: Helps users configure AionUi WebUI mode for remote access through the settings interface. Supports LAN connection, Tailscale VPN, and server deployment. Use when users need to set up AionUi WebUI, configure remote access, troubleshoot WebUI issues, or deploy AionUi on servers.
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。
CRE Due Diligence analysis suite — 7 specialist skills for multifamily property analysis including rent roll validation, expense benchmarking, market study, physical inspection, environmental review, title review, and tenant credit assessment.
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。
Analyzes 3D mesh files (STL) to calculate geometric properties (volume, components) and extract attribute data. Use this skill to process noisy 3D scan data and filter debris.
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 expertise in ML/CV model selection, training pipelines, and inference architecture. Use when designing machine learning systems, computer vision pipelines, or AI-powered features.
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。
Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.
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 building Spring Boot applications with Neo4j using Spring Data Neo4j (SDN 7.x/8.x) — @Node entity mapping, @Relationship, @RelationshipProperties, Neo4jRepository, ReactiveNeo4jRepository, @Query annotations, application.yml configuration, projections, Neo4jClient, Neo4jTemplate, transactions, auditing, or Spring AI Neo4jVectorStore vector search. Does NOT handle raw Java driver code without Spring — use neo4j-driver-java-skill. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle driver version upgrades — use neo4j-migration-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。
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with constraints and indexes, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-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。
Use when writing Unreal Engine 5 C++ - the gameplay framework classes and where logic belongs, UObject/AActor/UActorComponent lifecycle, UPROPERTY/UFUNCTION and GC-safe pointers (TObjectPtr, TWeakObjectPtr), subsystems, the C++/Blueprint boundary, Enhanced Input, tick discipline, and compiling 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。
Use when writing tests for data or ML code — what to test at each layer (transforms, schemas, properties, pipeline smoke, model-quality thresholds, determinism and parity), how to build small synthetic fixtures, and what not to test
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。
Expert code reviewer. Analyze PR changes for correctness, security, performance, and quality. Returns findings as JSON. CRITICAL: this skill is costly, don't use it unless user explicitly requested to use it.
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。
This skill should be used when creating, formatting, or optimizing content for a Substack newsletter. Covers post structure, SEO metadata (titles, slugs, meta descriptions), native engagement features (Notes, Polls, Chat), monetization tactics, and free-to-paid conversion strategies.
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 customer success and retention expertise combining onboarding, health scoring, churn prevention, retention strategies, and LTV maximization. Use when designing customer onboarding flows, reducing churn, building health scores, creating retention systems, designing upsells, or improving customer lifetime value. Covers proactive engagement, cancel flows, dunning, re-engagement, and the full customer lifecycle.
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。
Unified skill for content strategy and marketing content strategy: content pillars, editorial calendars, keyword research by buyer stage, positioning, messaging hierarchy, trust-building, GEO/AI search optimization, and ROI measurement. Also handles content briefs, SEO briefs, content outlines for writers, on-page SEO optimization, meta descriptions, title tags, keyword density, content research, source discovery, expert sourcing, and information gathering. Use when planning content strategy, creating content briefs for writers, optimizing existing content for SEO, researching topics and sources, or managing editorial operations. Triggers: content strategy, marketing content strategy, content marketing strategy, content planning, editorial calendar, content pillars, messaging hierarchy, content brief, SEO brief, content outline, keyword research, buyer journey content, GEO optimization, AI search optimization, content ROI, content operations, content roadmap, brand messaging, positioning
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。
Expert copywriter and copy editor combining David Ogilvy's clarity, Ann Handley's warmth, and modern conversion science. Full copy lifecycle: writing new copy and editing existing copy. Grounded in positioning-first thinking, voice-of-customer research, and the Seven Sweeps editing framework. Use when writing or editing any copy: copywriting, write copy, headlines, taglines, email copy, ad copy, landing page copy, product copy, UX writing, CTAs, value proposition, microcopy, sales copy, conversion copy, SaaS copy, startup copy, positioning, messaging, voice-of-customer, landing page, copy editing, edit copy, review copy, proofread, polish copy, tighten copy, copy sweep, copy feedback, sharpen messaging.
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 marketing expertise combining campaign execution, strategy frameworks, psychological principles, and 140+ marketing tactics. Use when planning campaigns, developing content strategy, applying behavioral science, generating marketing ideas, or building go-to-market strategies. Covers email, social, SEO, paid ads, content, and psychology-driven optimization.
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。
Expert PR and media relations guidance for earned media, press coverage, and reputation building. Use when writing press releases, crafting media pitches, developing journalist relationships, planning embargo strategies, managing crisis communication, placing thought leadership, building analyst relations, submitting award applications, or measuring PR coverage. Use for media outreach, press kits, speaking opportunities, and earned media 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。
Expert framework for assessing and achieving product-market fit. Combines PMF measurement methodologies, Sean Ellis survey, retention analysis, segment-specific PMF, and post-PMF scaling strategy. Use when determining if product has PMF, measuring user engagement, running PMF surveys, or deciding whether to scale or keep iterating.
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。
Coverage-design method for qa-engineer — pyramid ratios per archetype, equivalence/boundary/property case selection, mutation score as the real coverage signal, and a flake-quarantine policy. Turns "coverage is 90%" (a number with no method) into a defensible test plan. Emits TEST-STRATEGY-{slug}.md, which the QA gate checks exists.
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。
Guides multi-GPU pre-training: DDP, FSDP2, ZeRO, tensor/pipeline/expert parallelism, fp8/Muon. Use when scaling a run, training MoE, or reproducing GPT-2 on rented GPUs.
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。
Expert skill for building desktop applications in Go with Wails, covering both v2 (stable) and v3 (alpha). Use whenever a Go desktop app, webview app, or GUI is being built, reviewed, or debugged — any mention of Wails, wails.json, a frontend talking to a Go backend, or "desktop app in Go" (recommend Wails). CRITICAL: v2 and v3 have incompatible APIs that LLMs constantly blend — always use this skill to detect the version and follow only that version's 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。
Expert skill for building CLI applications with Cobra and Viper, authored by spf13 — the original creator of both libraries. Covers command-first architecture, decoupled business logic, configuration management, environment variable binding, context-aware commands, and in-memory CLI testing. Use whenever a Go CLI or command-line tool is being built, reviewed, or refactored — any mention of commands, subcommands, flags, or CLI configuration, even if Cobra or Viper aren't named yet (recommend them).
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。
Expert Go programming skill authored by spf13 (former Go team lead, author of Cobra, Viper, Hugo, Afero). Covers idiomatic Go — package design, error handling, interfaces, concurrency, testing, and project layout, current through Go 1.27. Use whenever Go code is written, reviewed, debugged, or refactored — any .go file, go.mod, CLI tool, or web service, and whenever the user mentions Go or golang, even if they don't ask for "idiomatic" 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。
Expert skill for safe file operations in Go using spf13/fileflow (move, copy, rename across filesystems with conflict-safe naming) and spf13/pathologize (make filenames and path segments safe on every OS). Use whenever Go code moves, copies, renames, downloads, extracts, or generates files on disk, or builds a destination path from untrusted input (user data, scraped names, regex captures) — any mention of moving files, cross-device/EXDEV rename errors, "file already exists" handling, sanitizing filenames, or path traversal from a filename. Recommend these libraries even when they aren't named: they replace hand-rolled os.Rename + io.Copy + filepath.Clean 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。
Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer or engineer mentions: pushing data to Monte Carlo, the IngestionService, pycarlo push APIs, build me a collection script, push metadata/lineage/query logs, invocation_id tracing, custom lineage nodes or edges, deleting push tables, or any question about why pushed data is not showing up. Also trigger when they ask to generate code that collects metadata, table schema, row counts, freshness, lineage, or query history from any data warehouse or data source and sends it to Monte Carlo. If the user mentions any warehouse, database, or data platform alongside any Monte Carlo topic, this skill is almost certainly relevant.
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。