Results for “source”

Guide for theming .NET MAUI apps — light/dark mode via AppThemeBinding, ResourceDictionary theme switching, DynamicResource bindings, system theme detection, and user theme preferences. Use when: "dark mode", "light mode", "theming", "AppThemeBinding", "theme switching", "ResourceDictionary theme", "dynamic resources", "system theme detection", "color scheme", "app theme", "DynamicResource". Do not use for: localization or language switching (see .NET MAUI localization documentation), accessibility visual adjustments (see .NET MAUI accessibility documentation), app icons or splash screens (see .NET MAUI app icons documentation), or Bootstrap-style class theming (see Plugin.Maui.BootstrapTheme NuGet package).

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Use when you need to write fast unit tests for Quarkus applications — including pure tests with @ExtendWith(MockitoExtension.class), @QuarkusTest with @InjectMock for full CDI mock replacement, @InjectSpy for partial CDI bean mocking, REST Assured for resource-focused tests, @ParameterizedTest with @CsvSource / @MethodSource, QuarkusTestProfile for test-specific configuration overrides, and naming conventions (*Test → Surefire, *IT → Failsafe). For framework-agnostic Java use @131-java-testing-unit-testing. This should trigger for requests such as Add or improve unit tests in a Quarkus project; Reduce slow @QuarkusTest usage with Mockito-first tests; Add @InjectSpy partial mocking or QuarkusTestProfile configuration in Quarkus tests; Convert repeated test methods to @ParameterizedTest with @CsvSource or @MethodSource; Write fast pure unit tests for Quarkus services. Part of Plinth Toolkit

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Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".

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CesiumJS entities and data sources - Entity, EntityCollection, DataSource, GeoJsonDataSource, KmlDataSource, CzmlDataSource, Graphics types, PathGraphics, PathMode, Visualizers. Use when adding points, labels, models, polygons, polylines, or time-segmented paths, loading GeoJSON/KML/CZML/GPX data, or working with the high-level Entity API.

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Adapt a historical primary source for classroom use — modifying complexity and length while preserving features for sourcing, close reading, and corroboration. Use when a primary source is too complex for the target age group.

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Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".

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Generate AI-friendly repository documentation with the SourceSage CLI. Use when Codex needs to run `sage` or `sourcesage` to create `.SourceSageAssets/Repository_summary.md`, analyze the current repository or another local repository, switch the output language between English and Japanese, use `--lite` to keep the summary small, change the output directory, or optionally create a deprecated tag-diff release report with `--diff`.

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Primary and secondary source analysis for historical reasoning. Covers source classification, sourcing (author/context/purpose), corroboration across multiple sources, contextualization within time and place, and bias detection. Use when evaluating historical evidence, assessing source reliability, or constructing evidence-based historical arguments.

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"Apply the Resource-Based View (Barney, 1991) and VRIO framework to evaluate whether a firm's resources and capabilities confer sustained competitive advantage. Use this skill when the user needs to assess internal resources for strategic value, determine if a competitive edge is sustainable, audit resource portfolios for VRIO criteria, or when they ask 'what makes our advantage sustainable', 'which resources matter most', or 'can competitors replicate this'.".

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Use for hands-on Pulumi CLI work: running deployments, fixing broken stacks, and managing infrastructure state. Handles: recovering from stuck or interrupted `pulumi up` with pending operations, cleaning orphaned resources from state after out-of-band cloud deletions, protecting critical resources from accidental `pulumi destroy`, moving resources between stacks without recreating them, targeting specific resources during deployment, migrating between backends (local file to Pulumi Cloud, S3), stack lifecycle management, state export/import/repair, CI/CD pipeline setup, and importing existing cloud resources. Use this skill — not the language-specific Pulumi skills — whenever the user's question is about operating, troubleshooting, or recovering Pulumi infrastructure rather than writing program code.

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Ingest supplied source material into an Obsidian vault with provenance and claim tracking: pasted text, files staged in the selected vault's inbox or .raw archive, or explicitly approved URLs. Use for a single source or bounded batch, not for saving an assistant answer. Triggers: ingest, ingest this file, ingest this URL, process this source, read and file this source, batch ingest, ingest these sources.

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Configure FSL Shifts, ShiftTemplates, ShiftPatterns, and Crew ServiceResources — availability windows layered on Operating Hours, bulk shift generation via ShiftPattern + ShiftPatternEntry, and the two Crew models (Static vs. Shell/Dynamic). NOT for setting up the resources themselves — types, skills, ResourcePreference — use admin/fsl-resource-management. NOT for capping how many hours or appointments a resource can take — use admin/fsl-capacity-planning.

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Use this skill to configure and manage Field Service Lightning workforce capacity — covering ServiceResourceCapacity for individual resource caps, WorkCapacityLimit for territory-level demand throttling, and reporting strategies for capacity vs. utilization analysis. NOT for resource skills, certifications, or preference setup — use admin/fsl-resource-management. NOT for work rules and service objectives — use admin/fsl-scheduling-policies. NOT for Omni-Channel agent capacity — use architect/omni-channel-capacity-model.

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Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.

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Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. Use when someone needs to understand or document how resources in an Azure resource group fit together.

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Create a capture for ANY Estuary connector using dynamic schema discovery. Use when the user wants to capture from a source that doesn't have a dedicated skill (e.g., Kafka, Salesforce, HubSpot, Stripe, S3, GCS, Kinesis, or any of the 148+ connectors). Use when user says "capture from <source>", "stream from <source>", "connect <source> to Estuary", or "set up <source> capture" and no connector-specific skill exists.

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Use when working with Azure Resource Manager — azure Resource Manager (ARM) template and deployment management. Covers template validation, deployment operations, resource group inspection, what-if analysis, deployment history, and template spec management. Use when deploying ARM templates, reviewing deployment status, analyzing resource groups, or troubleshooting failed deployments.

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Guide the user to add a data source, connection, or API connector to a Canvas App via Power Apps Studio, then verify and continue. USE WHEN the user asks to add a data source, add a connection, add an API, add a connector, connect to SharePoint / Dataverse / SQL / Excel / OneDrive / Teams / Office 365, or any similar request to make new data available to the app. DO NOT USE WHEN the user is asking to list or describe existing data sources — call list_data_sources or list_apis directly instead.

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This skill adds data(like resources) to OpenViking Context Database (aka. ov). Use when an agent needs to add files, data from URLs, or external knowledge during interactions. Trigger this tool when 1. is explicitly requested adding files or knowledge; 2. identifies valuable resources worth importing; 3. the user mentioned adding to OV/OpenViking/Context Database. This skill helps how to use CLI like `ov add-resource`, `ov add-skill` and `ov add-memory` to add resource data, skill files, memory files to OpenViking.

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Agent fallback for CDemoPlayer_SetIgnorePacketsForResourceLoading (auto-generated, category: vfunc). Locate CDemoPlayer::SetIgnorePacketsForResourceLoading in the CS2 engine module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CDemoPlayer_SetIgnorePacketsForResourceLoading, CDemoPlayer::SetIgnorePacketsForResourceLoading

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Import existing Azure resources into Terraform using Azure CLI discovery and Azure Verified Modules (AVM). Use when asked to reverse-engineer live Azure infrastructure, generate Infrastructure as Code from existing subscriptions/resource groups/resource IDs, map dependencies, derive exact import addresses from downloaded module source, prevent configuration drift, and produce AVM-based Terraform files ready for validation and planning across any Azure resource type.

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Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. Use this skill when the user asks for a diagram of their Azure resources or help in understanding how the resources relate to each other.

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AEM Cloud Service expert skill for Sling ResourceChangeListener. Covers the lightweight listener + JobConsumer pattern, migration from javax.jcr.observation.EventListener and resource-topic OSGi EventHandler, ResourceChangeListener vs ExternalResourceChangeListener decision, OSGi filter configuration, review checklist, troubleshooting (silent failures, hot-path blocking, missing service-user mapping), and common pitfalls.

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Investigate a question using official documentation, source code, specifications, and first-party APIs. A background agent records the findings in one Markdown file with sources for each claim, following the repository’s existing conventions for research notes.

• Verify API behavior against official sources
• Save research findings with citations
• Delegate reading while continuing other work