3,365 件 ・ 関連度順
概要と使いどころ
Use when the user asks to "track rankings" or "查排名"; measures keyword and SERP-position deltas over time from provided exports or connected tools, including AI-response checks. Not for multi-metric stakeholder reports or setting alerts — use performance-monitor (report or alert mode). 排名追踪/SERP监控
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Use when the user asks to "author our durable brand message hierarchy", "build the brand message house that seeds the canon", or "define the main narrative, three pillars, and tagline for the whole brand"; produces the DURABLE brand message system — main narrative, three value pillars, per-persona proof points (each labeled Measured / User-provided / '[needs source]'), and the tagline/one-liner — that seeds the narrative-registry canon and from which every per-launch house derives. Not for a single launch's message house or PR-FAQ — use message-house-builder; not for claim adjudication — use offer-claims-registry; not for the change-narrative arc itself — use strategic-narrative-designer. 品牌消息屋/主叙事/三支柱/标语/持久叙事 canon
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 asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP reputation trend from Postmaster + SNDS, a send-over-send delta with named regressions, and a reusable SEND-S placement snapshot on your own exported telemetry. Not for the pre-send SPF/DKIM/DMARC auth pre-flight — use deliverability-qa; not for computing the EQS or running the vetoes — use email-quality-auditor. 邮件收件箱落点监测/收件箱vs垃圾邮件/Postmaster声誉趋势
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。
Compile a structured literature survey on any AI/ML topic. Agent curates a research bundle (taxonomy + sections + bibliography of real papers) from a public anchor resource, then a chosen LLM generates the survey artifact. Output target is a wiki page (markdown), not a one-off HTML — survey lands in `<wiki>/derived/surveys/<slug>.md` with full bibliography rows in `sources.md`. Provider-agnostic (Anthropic/OpenAI/OpenRouter/Fireworks/custom OpenAI-compat). Use when the user asks for a "survey", "literature review", "lit review", or "deep dive" on a technical topic.
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。
Provider-agnostic multi-LLM deliberation. Three phases — independent responses, cross-model anonymized ranking, chairman synthesis. Credentials come from explicit plugin configuration or pro-workflow-specific CLI variables. Persists transcript to a wiki page when --wiki <slug> is passed. Use when the user wants multiple AI perspectives, consensus-building, or the "LLM Council" approach for high-stakes reviews, plan critique, or contested learning rules.
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。
Migrate workloads from Google Cloud Platform to AWS — plus AI and agentic workloads from any provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, migrate App Engine to Elastic Beanstalk, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform, app code, or billing exports, then clarify, design, estimate costs, generate artifacts, and collect feedback. Clarify must finish before Design, Estimate, or Generate. Do not use for: Azure migrations (see azure-to-aws), on-premises migrations, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, or GCP-to-GCP refactoring.
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。
AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references/` tree.
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。
Establishes VPC peering connections between two VPCs for direct private network connectivity. Always use this skill when creating or managing VPC peering — it validates CIDR overlap, updates all route tables in both VPCs, configures DNS resolution, and provides security group guidance that are critical for correct connectivity.
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。
Diagnoses and resolves Amazon RDS for Oracle connectivity, authentication, networking, and driver troubleshooting. Applicable to any RDS-for-Oracle question including connecting a Python Lambda to RDS Oracle in a VPC with pooling and cold-start optimization, EKS pods to RDS Oracle via the Secrets Manager CSI driver with IRSA and SecretProviderClass, ORA-12170 cross-VPC timeouts from EC2, DPI-1047 cannot-locate-64-bit-Oracle-Client errors, and Oracle Connection Manager (CMAN) on EC2 as a proxy with HA across two AZs. Covers python-oracledb thin vs thick mode, init_oracle_client, RDS Proxy does NOT support RDS Oracle, port 1521, VPC peering, Transit Gateway, Kerberos with AWS Managed Microsoft AD, SSL/TLS/NNE, SSM port forwarding, EC2/ECS Fargate/EKS/Lambda, SQL Developer/DBeaver/Toad/SQLcl, and Secrets 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。
Provides connectivity, authentication, and troubleshooting guidance for Amazon RDS for SQL Server. Applicable when users ask about SSMS times out connecting from EC2, Cannot generate SSPI context with Windows auth, connect RDS SQL Server from Lambda with pymssql, auth_scheme shows NTLM instead of KERBEROS on ECS Fargate, SSM tunnel to RDS SQL Server from laptop, port 1433 security group, TrustServerCertificate=True for localhost tunnels, SPN MSSQLSvc, AWS Managed Microsoft AD, CNAME not RDS endpoint for Kerberos, tds_version='7.4', encryption='require', port-as-string for pymssql, Secrets Manager credential caching in Lambda, error 18456 login failed. Covers Python (pymssql, pyodbc), .NET (Microsoft.Data.SqlClient), Java (JDBC mssql-jdbc), Node.js (tedious), IAM auth via RDS Proxy, and VPC/ECS/EKS/Lambda deployment.
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。
Provides authoritative compatibility checks, pricing estimates, connection troubleshooting, pre-warming guidance, and infrastructure mutations for Amazon Keyspaces (for Apache Cassandra). Covers LWT/batch operations, secondary indexes, materialized views, capacity modes, TTL, PITR, CDC, auto-scaling, multi-region keyspaces, UDTs, nodetool diagnostics parsing, SQL-to-Cassandra migration, and Cassandra-to-Keyspaces migration scenarios. Agents frequently produce incomplete or incorrect answers about Keyspaces feature support without this skill loaded.
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。
Provides authoritative guidance on Amazon Neptune Database and Neptune Analytics for graph, knowledge-graph, and relationship-heavy workloads — fraud detection / fraud rings, agentic memory / chatbot context across sessions, recommendations, identity resolution, Gremlin / openCypher / SPARQL queries, supernode / slow traversal, Neo4j to Neptune migration / APOC compatibility, Neptune Database vs Analytics engine selection, PageRank / community detection, GraphRAG, and connectivity from Lambda / EC2 / applications. Creates and modifies Neptune Database clusters/instances and Neptune Analytics graphs on explicit user confirmation; blocks destructive operations (delete, reset-graph, failover, major upgrade) and redirects to change-control.
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。
KubeKey (kk) Usage Guide. For Kubernetes cluster lifecycle management including creation, scaling and deletion. Use this skill whenever the user mentions kubekey, kk commands, cluster setup, cluster management, adding nodes, deleting nodes, creating inventory files, configuring clusters, installing Kubernetes, or deploying K8s. Also use this skill when the user asks about inventory.yaml, config.yaml formats, CNI configuration, container runtime setup, offline installation, or artifact operations. Provides detailed guidance on kk subcommand usage, config file formats, inventory structure and common 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。
为 codexhost 新增 Harness 插件，或规划、审查、补全现有 Harness Adapter。按当前公共契约实现原生能力，区分插件后端、预装发行和 Desktop 产品接入；不用于单纯添加 Model、Provider 或账号。
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。
Process use when you need to work with database indexing. This skill provides index design and optimization with comprehensive guidance and automation. Trigger with phrases like "create indexes", "optimize indexes", or "improve query performance".
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。
Execute use when you need to work with query optimization. This skill provides query performance analysis with comprehensive guidance and automation. Trigger with phrases like "optimize queries", "analyze performance", or "improve query speed".
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。
Collect a deterministic, secret-safe Alchemy diagnostic bundle for triage and escalation. Use when a provider issue needs reproducible evidence. Trigger with "Alchemy debug bundle", "collect Alchemy diagnostics", or "prepare an Alchemy support case".
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。
Generates images and game sprites through GPT or Grok with guided provider choices, separate saved defaults, automatic cleanup and optional curation. Handles sprite requests, ordinary image generation/editing, typography logos (로고, 타이포그래피, 타이틀 글자, 타이틀 로고, wordmark, logo, title lettering: a title screen drawn with the title in it, its lettering lifted out transparent), standalone image-to-video clips (i2v, animate this still, 그록 영상, 이매진 비디오, 스틸 움직여줘, first/last frame, reference-to-video, 영상 이어붙이기, 영상 편집, extend/edit a clip), clips from a video MCP on the agent (ZCRE, 지크 MCP), chroma removal, animation atlases, video loops, 큐레이션뷰, image candidates, 팔레트 스왑, palette swap, recolor, rig layers, engine exports, repeating backgrounds, projected shadows, motion/contact inspection and optional scene composition from existing assets.
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 the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.
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。
Turn a topic or finished script into a complete, publish-ready explainer video — led by an AI presenter from an authorized adult presenter image, or performed with no presenter in one of twelve explainer styles (nine visual styles and three narrative ones). Not for promos, ads, or footage montages. Use for new presenter or styled explainer videos and for continuing, revising, captioning, lip-sync repairing, or re-exporting an existing job. Use it whenever the user asks for 数字人口播 / 数字人讲解, for a 讲解视频 / 动画讲解 / 科普视频, asks which styles or templates are available (有哪些风格 / 看看风格 / 风格模板), or names one of the styles: 留白, 信号/科技感, 手帐/手绘, 立体书/纸艺, 波普漫画, 一镜到底/3D, 图纸与注脚, 黑板报, 黏土小城, 推演/动态图解, 案卷/调查复盘, 小剧场/生活场景. Keep model and provider selection capability-based and record the actual choices per job.
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。
Route broad or ambiguous AgentKit SEO work to the right module while keeping context scoped. Use when a request spans multiple surfaces, asks for overall digital-presence strategy, involves provider or install architecture, needs agent-context planning, or the correct platform skill is unclear.
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。
Work on Grida account and billing client adapters, credit display, Console handoffs and native execution receipts. Excludes financial policy and provider 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。
Grida AI agent system work: `@grida/daemon` (DaemonServer, loopback HTTP perimeter, files/workspaces, secrets store, daemon discovery) and `@grida/agent` (the agent tenant: sessions, providers/BYOK, runtime/tool execution, skills discovery, prompts, tiers, sandbox hosts). Use for `packages/grida-daemon/**`, `packages/grida-ai-agent/**`, desktop sidecar protocol changes, agent chat transport, and bugs in agent state or streams. For pure Electron window, preload, menu, deep-link, or CDP work, use `desktop`.
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, compare, and update shared AI model JSON for TypeScript, web, and Rust consumers. Covers text model tiers, image and video generation models, image tool models, release provenance, pricing data sourcing, and product-side catalogue cost estimates. Use when bumping model versions, adding new models, updating pricing, or auditing model specs against provider documentation.
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。