「sources」の検索結果

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。

Automated security scanner for external skill/agent content fetched from GitHub or web sources. Runs a 7-step PASS/FAIL security gate against fetched markdown/text content.

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 PE review of a submittal (shop drawings, product data, samples, equipment brochures) against specs, drawings, code questions and trade coordination. Produces findings with both sources, trade routing and a completeness gate. Triggers: 'review submittal', 'review shop drawings'.

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。

Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says "programmatic SEO", "pages at scale", "dynamic pages", "template pages", "generated pages", or "data-driven SEO".

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File a librarian query result back into the library as a new page with provenance tracking. Karpathy's "good answers can be filed back into the wiki as new pages" insight made concrete. The library compounds from explorations, not just from external sources.

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。

Rebuild the knowledge base shelf-index with hash-based change detection. Incremental by default — only re-extracts files whose content has changed since the last index. Use after ingesting new sources, after editing library files, or whenever the librarian agent reports a stale 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。

Health-check the project knowledge base. Looks for contradictions between files, stale claims that newer sources have superseded, orphan files with no inbound cross-references, important concepts mentioned but lacking their own page, missing cross-references, and data gaps. Returns a structured report; does not auto-fix.

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Investigate datasets and resolve entities using OpenPlanter methodology — cross-reference heterogeneous sources, build Admiralty/ACH confidence-tiered evidence chains, and apply OSINT tradecraft. Triggers on entity resolution, cross-reference datasets, evidence chain, OSINT investigation, structured investigation.

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。

Search the web and fetch page contents with Keenable AI — web search, page extraction, point-in-time queries, prompt-driven content extraction. Use when searching the web for current information, fetching webpage contents, extracting specific data from URLs, or researching topics with citations. Triggers on: web search, search the web, fetch page, read URL, find pages about, current information, Keenable, keen search, research with sources, look up, latest news, find information, check online, what is, who is.

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 sources need to be converted into a claim ledger with confidence levels.

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。

Agent Brain /brain-wiki: ingesting sources or updating durable project knowledge.

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, expand, revise, structure, and maintain a full Islamic University of Technology BSc thesis from source documents using the local iutbscthesis LaTeX template. Use when writing or editing thesis metadata, front matter, abstract, chapters, related works, methodology, results, discussion, conclusion, citations, appendices, figures, tables, code listings, or compile guidance for main.tex. Also use when the user expects an AI agent to turn papers, notes, PDFs, LaTeX sources, bib files, data tables, and assets into a substantial thesis manuscript chapter by chapter without requiring repeated babysitting.

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AI pressure redirection — handling conflicting demands, tool failures, and competing constraints by blending with incoming force then reframing. Use when receiving contradictory instructions from different sources, during tool failure cascades where the planned approach becomes unviable, when scope pressure threatens to expand the task beyond what was asked, or when user frustration or correction needs to be absorbed rather than deflected.

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。

Resolve merge and rebase conflicts with safe recovery strategies. Covers identifying conflict sources, reading conflict markers, choosing resolution strategies, and continuing or aborting operations safely. Use when a git merge, rebase, cherry-pick, or stash pop reports conflicts, when a git pull results in conflicting changes, or when you need to safely abort and restart a failed merge or rebase operation.

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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.

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Handcraft paper from plant fibres — fibre harvesting, pulping, sheet forming with a mould and deckle, pressing, and drying. Covers fibre sources (cotton, kozo, abaca, recycled paper), beating methods, sizing, and decorative techniques. Use when making handmade paper for art, stationery, or bookbinding, when creating unique textured or embedded paper for special projects, or when learning traditional paper making as a craft practice.

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Apply ant colony optimization and foraging theory to resource search, exploration-exploitation tradeoffs, and distributed discovery. Covers scout deployment, trail reinforcement, diminishing returns detection, and adaptive foraging strategy selection. Use when searching a large solution space where brute-force enumeration is impractical, balancing investment between exploring new approaches and deepening known good ones, optimizing resource allocation across uncertain opportunities, or diagnosing premature convergence on local optima.

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AI systematic knowledge acquisition from unfamiliar territory — deliberate model-building with feedback loops. Maps spaced repetition principles to AI reasoning: survey the territory, hypothesize structure, explore with probes, integrate findings, verify understanding, and consolidate for future retrieval. Use when encountering an unfamiliar codebase or domain, when a user asks about a topic requiring genuine investigation rather than recall, when multiple conflicting sources require building a coherent model, or when preparing to teach a topic and deep understanding is required first.

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Deploy applications to Kubernetes clusters using kubectl manifests for Deployments, Services, ConfigMaps, Secrets, and Ingress resources. Implement health checks, resource limits, rolling updates, and Helm chart packaging for production deployments. Use when deploying new applications to EKS, GKE, AKS, or self-hosted clusters, migrating from Docker Compose to container orchestration, implementing zero-downtime rolling updates, or setting up multi-environment deployments across dev, staging, and production.

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Analyze an arbitrary codebase to identify functions, APIs, and data sources suitable for exposure as MCP tools, producing a tool specification document. Use when planning an MCP server for an existing project, auditing a codebase before wrapping it as an AI-accessible tool surface, comparing what a codebase can do versus what is already exposed via MCP, or generating a tool spec to hand off to scaffold-mcp-server.

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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.

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Calculate and visualize magnetic fields produced by current distributions using the Biot-Savart law, Ampere's law, and magnetic dipole approximations. Use when computing B-fields from arbitrary current geometries, exploiting symmetry with Ampere's law, analyzing superposition of multiple sources, or characterizing magnetic materials through permeability, B-H curves, and hysteresis behavior.

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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。