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概要と使いどころ
Assesses upstream oil and gas assets with reserve estimation, production decline curves, and net asset value modeling. Use when evaluating E&P assets, analyzing reserve reports, or modeling upstream economics.
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Builds carbon credit models with offset generation analysis, verification costs, and market pricing dynamics for carbon-linked investments. Use when modeling carbon credits, analyzing offset economics, or evaluating carbon market exposure.
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。
Evaluates environmental liability exposure with remediation cost estimation, regulatory compliance requirements, and insurance coverage assessment. Use when analyzing environmental liabilities, estimating cleanup costs, or assessing environmental risk.
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。
Assesses timberland and agricultural investments with biological growth rates, harvest economics, and land value appreciation. Use when evaluating timber investments, analyzing farmland, or assessing biological asset returns.
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Assesses critical mineral investments with supply chain mapping, geopolitical risk, and processing infrastructure analysis. Use when evaluating critical minerals, analyzing lithium/cobalt supply, or assessing rare earth investments.
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。
Evaluates midstream assets with throughput analysis, fee-based vs commodity-exposed revenue, and contract structure assessment. Use when analyzing midstream investments, evaluating pipeline assets, or assessing gathering systems.
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。
Evaluates electricity market design with capacity payments, energy margins, ancillary services, and renewable intermittency management. Use when analyzing power markets, evaluating merchant exposure, or assessing capacity market dynamics.
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Evaluates OFS sector investments with rig count sensitivity, day rate analysis, and technology adoption curves. Use when analyzing oilfield services, evaluating service company economics, or assessing technology uptake.
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Evaluates asset retirement and decommissioning liabilities with cost estimation, timing analysis, and funding adequacy assessment. Use when analyzing decommissioning costs, evaluating ARO exposure, or assessing abandonment liability.
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。
Evaluates commodity price exposure with forward curve analysis, hedging strategies, and break-even price sensitivity. Use when analyzing commodity risk, designing hedging programs, or stress testing price assumptions.
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。
Verifies repository baseline test passing state and available memory/GPU resources to ensure safe mission execution.
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-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.
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。
Google Cloud CLI operations and resource management
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。
Profile and optimize Shiny application performance using profvis, bindCache, memoise, async/promises, debounce/throttle, and ExtendedTask for long-running computations. Use when the app feels slow or unresponsive during user interaction, when server resources are exhausted under concurrent load, when specific operations create bottlenecks, or when preparing an app for production deployment with many concurrent users.
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。
Forecast infrastructure and application metrics using Prophet or statsmodels for capacity planning, cost optimization, and proactive scaling. Visualize predictions in Grafana and set up alerts for projected resource exhaustion. Use when forecasting infrastructure capacity needs for CPU, memory, or disk, planning hardware procurement for next quarter, predicting cost trends to optimize cloud spending, or setting up proactive scaling policies based on predicted load.
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 an open-source agent framework for investment readiness by evaluating community health, supersession risk, architecture alignment, and governance sustainability. Produces a four-tier classification (INVEST / EVALUATE-FURTHER / CONTRIBUTE-CAUTIOUSLY / AVOID) to guide resource allocation decisions before committing engineering effort.
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Create a Work Breakdown Structure (WBS) and WBS Dictionary from project charter deliverables. Covers hierarchical decomposition, WBS coding, effort estimation, dependency identification, and critical path candidates. Use after a project charter is approved, when planning a classic or waterfall project with defined deliverables, breaking a large initiative into manageable work packages, or establishing a basis for effort estimation and resource planning.
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 a custom MCP (Model Context Protocol) server that exposes domain-specific tools to AI assistants. Covers server implementation in Node.js or R, tool definitions, the resources and prompts primitives, transport configuration, and testing with Claude Code. Use when you need to expose custom functionality beyond what mcptools provides, when building specialized domain-specific AI integrations, or when wrapping existing APIs or services as MCP 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。
Modern C# idioms for any .NET project (C# 10+, .NET 6+): nullable reference types, records, readonly structs, primary constructors, pattern matching, async/await with CancellationToken, IDisposable/IAsyncDisposable, file-scoped namespaces, var usage, naming conventions (PascalCase members, _camelCase fields, I-prefixed interfaces), and class design rules. Apply whenever the project is a .NET 6+ project. Stack-agnostic — referenced by every .NET plugin in the marketplace. Use this skill to: - Write self-documenting immutable value types with records and readonly structs. - Handle nullable reference types explicitly to eliminate NullReferenceException at compile time. - Implement async/await correctly with CancellationToken propagation and ConfigureAwait(false) in libraries. - Dispose unmanaged resources correctly via IDisposable / IAsyncDisposable and using statements. - Apply C# pattern matching (switch expressions, property patterns, list patterns) for cleaner branching logic. Do NOT use this skill for: - Framework-specific idioms (ASP.NET Core controllers, minimal APIs, EF Core — those live in aspnet-core-plugin skills). - Build tooling (dotnet CLI, NuGet, csproj) — see csharp-foundation:dotnet-tooling. - Testing patterns — see csharp-foundation:dotnet-testing.
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。
Modern Python idioms for any Python 3.10+ project: PEP 8 style, PEP 484/526 type hints, dataclasses, pathlib, enums, f-strings, structural pattern matching (match/case), context managers, exception handling, and null discipline. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Write strongly-typed code with type hints on every function signature and class attribute. - Replace isinstance chains and magic constants with match/case and enums. - Use dataclasses or NamedTuple for value objects and data containers. - Handle resources safely with context managers and pathlib for all file paths. - Apply PEP 8 naming and structure conventions consistently. Do NOT use this skill for: - Framework-specific idioms (Django ORM, FastAPI routers, Flask blueprints — those live in framework plugin skills). - Packaging and dependency management — see python-foundation:python-tooling. - Testing patterns — see python-foundation:pytest-testing.
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。
Implement or extend one governed Proto UI Module semantic slice. Use when Module ownership, facade and port boundary, dependencies, resource lifetime, Host Capability plan, Runtime registration, Adapter evidence, and validation scope are fixed by current authority. Do not use to admit a new Module or decide ownership.
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 — including AI and agentic workloads regardless of cloud 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, Google Cloud migration, 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 files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.
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 these skills to manage and monitor Oracle databases by executing SQL statements, exploring schema metadata, analyzing query performance, monitoring active sessions and resource consumption, and managing storage and object health.
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 whenever the user mentions Betaflight, FPV drone firmware, flight-controller config, PID/filter/rates tuning, or blackbox log analysis — or shares a Betaflight artifact: a CLI diff/dump (lines like 'diff all', 'set ', 'feature ', 'resource ') or a .bbl/.bfl blackbox log, even when not named as such — or runs a chirp tuning session via Sweep Studio / FPVLogForge (a chirp log ID to analyse, 'analyse log', 'résultat chirp', iterative Bode/step/Ms tuning). Covers flight symptoms (oscillations, wobble, propwash, jello, hot motors, drift), motor/ESC and RX/ELRS/CRSF setup, builds from 3" to 10" (cinewhoop, tinywhoop, longrange, X-class), version migrations (4.4 → 4.5 → 4.6), and configuring a new drone from scratch (setup wizard). Trigger even when phrased casually ("mon drone wobble", "PID help", "config FC") — under-triggering is worse than over-triggering.
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。