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概要と使いどころ
Review FriendlyBet quality, regression risk, test plans, release readiness, version bump discipline, scoring/locking correctness, provider fallback behavior, and dirty-worktree safety. Use before shipping app code, scoring changes, migrations, sports integrations, copy updates, PWA cache changes, or any risky user-facing flow.
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。
Model sports rules, event formats, prediction types, scoring implications, lock rules, data requirements, and provider constraints for FriendlyBet. Use when adding or comparing sports such as football, basketball, American football, tennis, tournaments, leagues, playoffs, brackets, weekly picks, or World Cup-specific logic.
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。
Scan downstream specs for contradictions with locked decisions and apply approved fixes with consistency checks
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。
Assess pipeline layer state, detect prerequisite blockers, classify audit status, and persist remediation plan
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。
Draft IA shard sections from reconciled ideation and architecture sources, with write-as-you-go section locking
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。
Senior Kotlin specialist code review — framework-agnostic. Use whenever the user asks to review, audit, critique, or get feedback on Kotlin code, a file, a class, a function, a module, a diff, a branch, a commit, or a pull request. Judges Kotlin language idioms, logic correctness, architecture and layering, concurrency (coroutines, Flow, structured concurrency, cancellation, race conditions), null safety, exception safety, testability, performance, and security. Detects force-unwraps, unchecked casts, GlobalScope, leaked mutability, broken structured concurrency, hidden side effects, weak abstractions, untestable seams, allocation hot spots, weak crypto, input-validation gaps, and PII logging. Outputs prioritized findings with file:line anchors and minimal-diff fixes. No assumptions about DI framework, UI framework, or build system.
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。
How to run and test the docs/index.html AGSL shader web gallery locally (static server, WebGL2-capable Chrome flags, CDP verification hooks).
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 this skill when working on camera, gallery, file pick/upload/download, file preview, sharing, or filesystem-backed media. For Preferences keys, use mobile-local-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。
Bu template'in tasarim sistemi referansi — renk (colorScheme + AppThemeColors semantic token'lari), tipografi (textTheme slotlari, Poppins/Inter), spacing/radius/golge/sure token'lari (AppPaddings, AppRadius, AppShadows, AppDurations, AppIconSizes), paylasilan widget katalogu (AppPrimaryButton, dort-durum widget'lari, AppTextField, sheet'ler), 8 varyantli light/dark tema ve easy_localization. Kullanici UI yazarken/duzenlerken "renkleri projeye gore kullan", "bu butonu projeye gore yaz", "hangi spacing/radius", "tasarim sistemine uydur", "style guide", "tema token'lari" dediginde kullan.
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 deploying or managing an app that uses Prisma Composer (`@prisma/composer`): wiring its services and Modules, running it locally, testing composed services, or standing up / tearing down an environment. Triggers on "prisma composer", "@prisma/composer", "prisma app", `prisma deploy`, `prisma dev`, `compute()`, `module()`, `contract()`, `service.load()`, `mockService`, `bootstrapService`.
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。
Cuts the next minor release of Prisma Composer: bumps the root package.json version, propagates it to every workspace package in lockstep, and opens a PR titled "chore(release): v<next-version>". When a maintainer merges the PR, the `Publish to npm` workflow runs automatically and ships the new version to npm under dist-tag `latest`, plus a matching GitHub Release with auto-generated notes. Use when a maintainer asks to "cut the next minor", "bump to the next version", "open a release PR", or "prepare a publish 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。
AI Personal Assistant network skill. Use when: contacting another PA, coordinating with peer agents, scheduling meetings between owners, broadcasting messages, looking up contacts from the local PA directory, or performing any cross-PA task. Reads contact data from data/pa-directory.json in the workspace. Does NOT contain hardcoded contact data — each PA maintains their own directory file.
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 Personal Assistant network skill for multi-agent PA coordination. Use when: contacting another PA, coordinating with peer agents, scheduling meetings between owners, broadcasting messages to PA groups, or looking up contacts from the local PA directory. Reads contact data from data/pa-directory.json in the workspace.
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。
Reduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
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 data/commitments.jsonl (flat list) into a who-owes-what-to-whom graph. Surfaces overdue chains and cross-PA dependencies that the flat list hides. Triggers: "what's overdue", "what did X promise", "commitment graph", "who's blocking whom".
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。
Transcribe WhatsApp voice messages using local Whisper CLI. Use when: owner or contact sends an audio/ogg voice message. Combines Whisper transcription + CRM update + task creation. Works offline for short clips, uses OpenAI API for long clips. Hebrew and English supported.
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 working with Contentful — contentful headless CMS management covering space and environment inventory, content type analysis, entry and asset monitoring, locale configuration, webhook tracking, API key auditing, and usage quota monitoring. Use when reviewing content models, investigating publishing issues, monitoring API usage, or auditing space access.
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 working with Device42 — device42 IT infrastructure management covering data center infrastructure management (DCIM), application dependency mapping, IP address management, and asset lifecycle tracking. Use when documenting data center rack layouts and power chains, mapping application dependencies and communication flows, managing IP address allocation and subnets, or tracking hardware assets from procurement through decommission.
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 working with Consul Kv — consul KV store management, key namespace analysis, session/lock inspection, and watch configuration. Covers KV tree structure, key count by prefix, session health, prepared queries, and transaction support diagnostics. Read this skill before any Consul KV operations.
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 working with Coreweave — coreWeave GPU cloud management covering Kubernetes namespace inventory, GPU workload status, virtual server instances, persistent volume claims, node allocation, billing analysis, and network configuration. Use for comprehensive CoreWeave infrastructure assessment and GPU workload 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。
Use when working with Changesets — changesets version management covering changeset file inventory, pending version bump analysis, package release readiness, changelog generation status, and monorepo release coordination. Use when auditing pending changesets, investigating release blockers, reviewing version bump strategies, or managing multi-package release workflows.
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 working with Close Crm — close CRM management including leads, contacts, opportunities, activities, sequences, smart views, and custom fields. Covers pipeline velocity, calling metrics, email outreach performance, sequence engagement, and team productivity 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 working with Banana Dev — banana.dev ML inference platform management covering model inventory, deployment status, API call history, GPU allocation, scaling configuration, build logs, and latency metrics. Use for comprehensive Banana.dev model deployment assessment and inference performance 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 working with Azure Container Instances — azure Container Instances management covering container group inventory, container status and restart counts, CPU and memory utilization, networking configuration, log retrieval, and GPU allocation tracking. Use for ACI workload monitoring and troubleshooting.
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。