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概要と使いどころ
Configure Claude API across dev, staging, and production environments with isolated keys, model routing, and spend controls per environment. Trigger with phrases like "anthropic environments", "claude multi-env", "anthropic staging setup", "claude dev vs prod config".
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。
Production-grade architecture patterns for Apify-powered applications. Use when designing scraping infrastructure, building multi-Actor pipelines, or integrating Apify into a larger system architecture. Trigger with "apify architecture", "apify best practices", "apify project structure", "scraping architecture", "apify system 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。
Optimize Claude API performance with prompt caching, model selection, streaming, and latency reduction techniques. Use when experiencing slow responses, optimizing token usage, or reducing time-to-first-token in production. Trigger with phrases like "anthropic performance", "claude speed", "optimize claude latency", "anthropic caching", "faster claude responses".
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。
Apply production-ready patterns for the Anima SDK design-to-code pipeline. Use when building reusable Anima client wrappers, implementing output caching, or establishing team standards for design-to-code automation. Trigger with: "anima SDK patterns", "anima best practices", "anima code patterns".
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。
Optimize Anima code generation performance with caching, parallelism, and output tuning. Use when reducing generation latency, optimizing batch component generation, or improving generated code quality for production use. Trigger with: "anima performance", "anima slow", "anima optimization", "anima caching".
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 isolated Algolia development, staging, preview, and production targets with explicit promotion rules. Use when environments share credentials or index names, or previews need bounded search data. Trigger with "Algolia environments", "Algolia staging setup", or "preview index".
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 production-grade agent .md files aligned with the current Anthropic subagent contract. Also validates existing agents against the marketplace compliance rules. Use when building custom subagents, reviewing agent quality, or creating parallel agent architectures for orchestrator skills. Trigger with "/agent-creator", "create an agent", "build a subagent", or "validate my agent". Make sure to use this skill whenever creating agents/*.md files for plugins or standalone use.
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 and optimize an Algolia search path using repository and production evidence instead of universal latency targets. Use when search feels slow, payloads are large, or rendering regresses. Trigger with "tune Algolia performance", "slow Algolia search", or "search latency".
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 and review a bounded CI gate for Algolia index configuration and disposable-index smoke tests. Use when search changes need pull-request evidence without mutating production. Trigger with "Algolia CI", "test Algolia in GitHub Actions", or "search deployment gate".
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。
Plan and execute a reversible migration from another search system or legacy index design to Algolia. Use when translating schemas, queries, relevance behavior, or production traffic. Trigger with "migrate to Algolia", "Algolia cutover", or "search engine migration".
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。
Deploy an Alchemy-backed service through environment-scoped credentials, chain assertions, canaries, and rollback gates. Use when promoting an integration to hosted environments. Trigger with "deploy Alchemy integration", "Alchemy production deploy", or "promote an Alchemy service".
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 a production Alchemy architecture with capability-specific adapters, explicit trust boundaries, partial-state semantics, and reversible operations. Use when reviewing or creating an Alchemy-backed system. Trigger with "Alchemy architecture", "design an Alchemy dApp backend", or "review Alchemy boundaries".
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。
Plan and verify deployment of an Algolia-backed application with separated browser and server credentials. Use when releasing search code, index configuration, or event instrumentation. Trigger with "deploy Algolia", "Algolia production rollout", or "search release checklist".
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。
Prove one Adobe API connection with a current, read-only or synthetic operation and a content-safe receipt. Use during onboarding before any production workflow. Use when the task requires adobe minimal access proof. Trigger with "Adobe hello world", "test Adobe connection", or "verify Adobe entitlement".
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。
Scaffold production-ready AI agents on Google's Agent Development Kit (ADK): ReAct-style single agents, multi-agent orchestration (Sequential/Parallel/Loop), tool wiring, evaluation, and optional Vertex AI Agent Engine deployment. Use when building, scaffolding, or deploying ADK agents on Google Cloud, or when wiring ADK tools and orchestration patterns. Trigger with "build an ADK agent", "scaffold an agent on ADK", or "deploy to Agent Engine".
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。
Detect current high-risk Adobe integration traps before they become production incidents. Use when the task requires adobe integration pitfall review. Trigger with "Adobe pitfalls", "review Adobe integration", or "find obsolete Adobe 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。
Define a production Adobe architecture spanning identity, service adapters, async workers, asset custody, I/O Events, App Builder, evidence, and recovery. Use when the task requires adobe integration reference architecture. Trigger with "design Adobe architecture", "Adobe reference architecture", or "standardize Adobe services".
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 software engineer specializing in creating production-ready ADK agents with best practices, code structure, testing, and deployment automation. Use when asked to "build ADK agent", "create agent code", or "engineer ADK application". Trigger with relevant phrases based on skill purpose.
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。
Separate Adobe development, stage, and production organizations/projects/workspaces, credentials, profiles, storage, events, budgets, and evidence. Use when the task requires adobe multi-environment isolation. Trigger with "Adobe environments", "separate Adobe staging", or "Adobe workspace setup".
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。
Organization-grade identity-fabric mapping: tenant/federation fingerprinting and the pre-auth user-ENUMERATION oracle methodology — enumeration and fingerprint only, never credential submission. Covers domain-to-tenant resolution (Microsoft getuserrealm.srf Managed/Federated namespace check, Entra OIDC metadata tenant-GUID extraction, Autodiscover v2), keyless Microsoft tenant-federation mapping (GetFederationInformation SOAP -> sibling-domain discovery, discover-only ROE, FEDERATED_WITH provenance edge held out of attack-path pivoting), Okta org-slug derivation + OIDC fingerprint + governed custom-domain enumeration, ADFS passive/active fingerprint + version inference, Google Workspace MX-correlated detection, generic OIDC (Auth0/Keycloak/Ping Identity/OneLogin/Duo) discovery, SAML metadata (5 paths), Azure AD Seamless-SSO Negotiate-challenge detection, Microsoft Defender for Identity (MDI) sensor-API presence check, the user-enumeration oracle methodology for Microsoft GetCredentialType (IfExistsResult semantics: exists / doesn't-exist / exists-in-federated-tenant / throttled) and Okta /api/v1/authn (errorCode differential), Medium-detectability discipline with a hard 20-candidate-per-tenant cap and admin/role interest-based ranking, and name x confirmed-email-pattern login-candidate synthesis that FAILS CLOSED with zero output when no org pattern is confirmed. Grounded directly in a production ASM implementation's sso_idp.py, tenant_recon.py, and core/email_patterns.py modules. Deepens — does not duplicate — offensive-osint skill's Identity Fabric endpoint reference with the tenant-federation MAP, the oracle WORKFLOW, and the candidate-SYNTHESIS methodology that reference lacks. Use when fingerprinting an organization's identity provider, mapping its tenant/federation boundary, running an authorized pre-auth user-enumeration pass, or synthesizing login candidates from harvested names to feed that oracle — never for password spray, credential submission, or auth bypass.
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。
Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.
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。
Verify and release Three.js browser games: playtest QA, automated bot playtests, mobile and responsive checks, production builds, static-hosting base paths, debug gating, bundle review, screenshots, visual regression baselines, canvas-pixel inspection with measured metrics, and release risk reports.
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。
Manage for output using Grove's "High Output Management": a manager's output is their organization's output, raised by high-leverage activities. Use when the user mentions "high output management", "managerial leverage", "one-on-ones", "1:1 agenda", "OKRs", "performance review", "task-relevant maturity", "delegation", "meeting overload", "new manager", "how do I run a 1:1", or "just got promoted to manager". Also trigger when structuring a manager's calendar and meeting cadence, designing team metrics, running planning, coaching delegation, or preparing performance reviews. Covers leverage, production principles, meetings as the medium of management, decisions, OKRs, and task-relevant maturity. For intrinsic motivation, see drive-motivation. For a company operating system, see traction-eos.
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。
Guided journey from a working-but-untested vibe-coded prototype to a production-ready product with tests, clean structure, a business-rules boundary, and resilience at scale. Orchestrates nine skills phase by phase - working-with-legacy-code, clean-code, refactoring-patterns, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, system-design, ddia-systems - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, IMPROVE-CODE-QUALITY-PLAN.md) so the journey resumes across sessions. Use when the user wants to harden an AI-generated prototype, add tests before refactoring, make code safe to change, or says 'this works on my machine but I am scared to touch it'. For an aged codebase, remove-technical-debt; for greenfield structure, design-code-architecture; for a product and UX pass, improve-app; to optimize speed and structure, architecture-optimization. For one framework in isolation, invoke that skill directly.
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。