docs: update skill descriptions and fix formatting in markdown files

This commit is contained in:
Ares
2026-02-25 15:02:20 +00:00
committed by sck_0
parent 6722218221
commit bd3dae68cb
216 changed files with 337 additions and 216 deletions

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@@ -1,6 +1,7 @@
---
name: ai-engineer
description: "Build production-ready LLM applications, advanced RAG systems, and"
description: |
Build production-ready LLM applications, advanced RAG systems, and
intelligent agents. Implements vector search, multimodal AI, agent
orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM
features, chatbots, AI agents, or AI-powered applications.
@@ -9,6 +10,7 @@ metadata:
risk: unknown
source: community
---
You are an AI engineer specializing in production-grade LLM applications, generative AI systems, and intelligent agent architectures.
## Use this skill when
@@ -37,11 +39,13 @@ You are an AI engineer specializing in production-grade LLM applications, genera
- Add guardrails for prompt injection, PII, and policy compliance.
## Purpose
Expert AI engineer specializing in LLM application development, RAG systems, and AI agent architectures. Masters both traditional and cutting-edge generative AI patterns, with deep knowledge of the modern AI stack including vector databases, embedding models, agent frameworks, and multimodal AI systems.
## Capabilities
### LLM Integration & Model Management
- OpenAI GPT-4o/4o-mini, o1-preview, o1-mini with function calling and structured outputs
- Anthropic Claude 4.5 Sonnet/Haiku, Claude 4.1 Opus with tool use and computer use
- Open-source models: Llama 3.1/3.2, Mixtral 8x7B/8x22B, Qwen 2.5, DeepSeek-V2
@@ -51,6 +55,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Cost optimization through model selection and caching strategies
### Advanced RAG Systems
- Production RAG architectures with multi-stage retrieval pipelines
- Vector databases: Pinecone, Qdrant, Weaviate, Chroma, Milvus, pgvector
- Embedding models: OpenAI text-embedding-3-large/small, Cohere embed-v3, BGE-large
@@ -62,6 +67,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Advanced RAG patterns: GraphRAG, HyDE, RAG-Fusion, self-RAG
### Agent Frameworks & Orchestration
- LangChain/LangGraph for complex agent workflows and state management
- LlamaIndex for data-centric AI applications and advanced retrieval
- CrewAI for multi-agent collaboration and specialized agent roles
@@ -72,6 +78,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Agent evaluation and monitoring with custom metrics
### Vector Search & Embeddings
- Embedding model selection and fine-tuning for domain-specific tasks
- Vector indexing strategies: HNSW, IVF, LSH for different scale requirements
- Similarity metrics: cosine, dot product, Euclidean for various use cases
@@ -80,6 +87,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Vector database optimization: indexing, sharding, and caching strategies
### Prompt Engineering & Optimization
- Advanced prompting techniques: chain-of-thought, tree-of-thoughts, self-consistency
- Few-shot and in-context learning optimization
- Prompt templates with dynamic variable injection and conditioning
@@ -89,6 +97,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Multi-modal prompting for vision and audio models
### Production AI Systems
- LLM serving with FastAPI, async processing, and load balancing
- Streaming responses and real-time inference optimization
- Caching strategies: semantic caching, response memoization, embedding caching
@@ -98,6 +107,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Observability: logging, metrics, tracing with LangSmith, Phoenix, Weights & Biases
### Multimodal AI Integration
- Vision models: GPT-4V, Claude 4 Vision, LLaVA, CLIP for image understanding
- Audio processing: Whisper for speech-to-text, ElevenLabs for text-to-speech
- Document AI: OCR, table extraction, layout understanding with models like LayoutLM
@@ -105,6 +115,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Cross-modal embeddings and unified vector spaces
### AI Safety & Governance
- Content moderation with OpenAI Moderation API and custom classifiers
- Prompt injection detection and prevention strategies
- PII detection and redaction in AI workflows
@@ -113,6 +124,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Responsible AI practices and ethical considerations
### Data Processing & Pipeline Management
- Document processing: PDF extraction, web scraping, API integrations
- Data preprocessing: cleaning, normalization, deduplication
- Pipeline orchestration with Apache Airflow, Dagster, Prefect
@@ -121,6 +133,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- ETL/ELT processes for AI data preparation
### Integration & API Development
- RESTful API design for AI services with FastAPI, Flask
- GraphQL APIs for flexible AI data querying
- Webhook integration and event-driven architectures
@@ -129,6 +142,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- API security: OAuth, JWT, API key management
## Behavioral Traits
- Prioritizes production reliability and scalability over proof-of-concept implementations
- Implements comprehensive error handling and graceful degradation
- Focuses on cost optimization and efficient resource utilization
@@ -141,6 +155,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Balances cutting-edge techniques with proven, stable solutions
## Knowledge Base
- Latest LLM developments and model capabilities (GPT-4o, Claude 4.5, Llama 3.2)
- Modern vector database architectures and optimization techniques
- Production AI system design patterns and best practices
@@ -153,6 +168,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
- Prompt engineering and optimization methodologies
## Response Approach
1. **Analyze AI requirements** for production scalability and reliability
2. **Design system architecture** with appropriate AI components and data flow
3. **Implement production-ready code** with comprehensive error handling
@@ -163,6 +179,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
8. **Provide testing strategies** including adversarial and edge cases
## Example Interactions
- "Build a production RAG system for enterprise knowledge base with hybrid search"
- "Implement a multi-agent customer service system with escalation workflows"
- "Design a cost-optimized LLM inference pipeline with caching and load balancing"

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---
name: analytics-tracking
description: ">"
description: >
Design, audit, and improve analytics tracking systems that produce reliable,
decision-ready data. Use when the user wants to set up, fix, or evaluate
analytics tracking (GA4, GTM, product analytics, events, conversions, UTMs).

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---
name: angular
description: ">-"
description: >-
Modern Angular (v20+) expert with deep knowledge of Signals, Standalone
Components, Zoneless applications, SSR/Hydration, and reactive patterns.
Use PROACTIVELY for Angular development, component architecture, state

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---
name: api-documenter
description: "Master API documentation with OpenAPI 3.1, AI-powered tools, and"
description: |
Master API documentation with OpenAPI 3.1, AI-powered tools, and
modern developer experience practices. Create interactive docs, generate SDKs,
and build comprehensive developer portals. Use PROACTIVELY for API
documentation or developer portal creation.

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---
name: arm-cortex-expert
description: ">"
description: >
Senior embedded software engineer specializing in firmware and driver
development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD).
Decades of experience writing reliable, optimized, and maintainable embedded

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---
name: azure-ai-agents-persistent-dotnet
description: "|"
description: |
Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: "PersistentAgentsClient", "persistent agents", "agent threads", "agent runs", "streaming agents", "function calling agents .NET".
package: Azure.AI.Agents.Persistent
risk: unknown

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---
name: azure-ai-agents-persistent-java
description: "|"
description: |
Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
Triggers: "PersistentAgentsClient", "persistent agents java", "agent threads java", "agent runs java", "streaming agents java".
package: com.azure:azure-ai-agents-persistent

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---
name: azure-ai-contentsafety-py
description: "|"
description: |
Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.
Triggers: "azure-ai-contentsafety", "ContentSafetyClient", "content moderation", "harmful content", "text analysis", "image analysis".
package: azure-ai-contentsafety

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---
name: azure-ai-contentunderstanding-py
description: "|"
description: |
Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.
Triggers: "azure-ai-contentunderstanding", "ContentUnderstandingClient", "multimodal analysis", "document extraction", "video analysis", "audio transcription".
package: azure-ai-contentunderstanding

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---
name: azure-ai-document-intelligence-dotnet
description: "|"
description: |
Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".
package: Azure.AI.DocumentIntelligence
risk: unknown

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---
name: azure-ai-ml-py
description: "|"
description: |
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
Triggers: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
package: azure-ai-ml

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---
name: azure-ai-openai-dotnet
description: "|"
description: |
Azure OpenAI SDK for .NET. Client library for Azure OpenAI and OpenAI services. Use for chat completions, embeddings, image generation, audio transcription, and assistants. Triggers: "Azure OpenAI", "AzureOpenAIClient", "ChatClient", "chat completions .NET", "GPT-4", "embeddings", "DALL-E", "Whisper", "OpenAI .NET".
package: Azure.AI.OpenAI
risk: unknown

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---
name: azure-ai-projects-dotnet
description: "|"
description: |
Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".
package: Azure.AI.Projects
risk: unknown

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---
name: azure-ai-projects-java
description: "|"
description: |
Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.
Triggers: "AIProjectClient java", "azure ai projects java", "Foundry project java", "ConnectionsClient", "DatasetsClient", "IndexesClient".
package: com.azure:azure-ai-projects

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---
name: azure-ai-textanalytics-py
description: "|"
description: |
Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
Triggers: "text analytics", "sentiment analysis", "entity recognition", "key phrase", "PII detection", "TextAnalyticsClient".
package: azure-ai-textanalytics

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---
name: azure-ai-transcription-py
description: "|"
description: |
Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.
Triggers: "transcription", "speech to text", "Azure AI Transcription", "TranscriptionClient".
package: azure-ai-transcription

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---
name: azure-ai-translation-document-py
description: "|"
description: |
Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale.
Triggers: "document translation", "batch translation", "translate documents", "DocumentTranslationClient".
package: azure-ai-translation-document

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---
name: azure-ai-translation-text-py
description: "|"
description: |
Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.
Triggers: "text translation", "translator", "translate text", "transliterate", "TextTranslationClient".
package: azure-ai-translation-text

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---
name: azure-ai-vision-imageanalysis-py
description: "|"
description: |
Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks.
Triggers: "image analysis", "computer vision", "OCR", "object detection", "ImageAnalysisClient", "image caption".
package: azure-ai-vision-imageanalysis

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---
name: azure-ai-voicelive-dotnet
description: "|"
description: |
Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant .NET", "bidirectional audio", "speech-to-speech".
package: Azure.AI.VoiceLive
risk: unknown

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---
name: azure-ai-voicelive-java
description: "|"
description: |
Azure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket.
Triggers: "VoiceLiveClient java", "voice assistant java", "real-time voice java", "audio streaming java", "voice activity detection java".
package: com.azure:azure-ai-voicelive

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---
name: azure-ai-voicelive-ts
description: "|"
description: |
Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots in Node.js or browser environments. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant TypeScript", "bidirectional audio", "speech-to-speech JavaScript".
package: "@azure/ai-voicelive"
risk: unknown

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---
name: azure-appconfiguration-java
description: "|"
description: |
Azure App Configuration SDK for Java. Centralized application configuration management with key-value settings, feature flags, and snapshots.
Triggers: "ConfigurationClient java", "app configuration java", "feature flag java", "configuration setting java", "azure config java".
package: com.azure:azure-data-appconfiguration

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---
name: azure-appconfiguration-py
description: "|"
description: |
Azure App Configuration SDK for Python. Use for centralized configuration management, feature flags, and dynamic settings.
Triggers: "azure-appconfiguration", "AzureAppConfigurationClient", "feature flags", "configuration", "key-value settings".
package: azure-appconfiguration

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---
name: azure-compute-batch-java
description: "|"
description: |
Azure Batch SDK for Java. Run large-scale parallel and HPC batch jobs with pools, jobs, tasks, and compute nodes.
Triggers: "BatchClient java", "azure batch java", "batch pool java", "batch job java", "HPC java", "parallel computing java".
risk: unknown

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---
name: azure-containerregistry-py
description: "|"
description: |
Azure Container Registry SDK for Python. Use for managing container images, artifacts, and repositories.
Triggers: "azure-containerregistry", "ContainerRegistryClient", "container images", "docker registry", "ACR".
package: azure-containerregistry

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---
name: azure-cosmos-java
description: "|"
description: |
Azure Cosmos DB SDK for Java. NoSQL database operations with global distribution, multi-model support, and reactive patterns.
Triggers: "CosmosClient java", "CosmosAsyncClient", "cosmos database java", "cosmosdb java", "document database java".
package: azure-cosmos

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---
name: azure-cosmos-py
description: "|"
description: |
Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
Triggers: "cosmos db", "CosmosClient", "container", "document", "NoSQL", "partition key".
package: azure-cosmos

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---
name: azure-cosmos-rust
description: "|"
description: |
Azure Cosmos DB SDK for Rust (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
Triggers: "cosmos db rust", "CosmosClient rust", "container", "document rust", "NoSQL rust", "partition key".
package: azure_data_cosmos

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---
name: azure-cosmos-ts
description: "|"
description: |
Azure Cosmos DB JavaScript/TypeScript SDK (@azure/cosmos) for data plane operations. Use for CRUD operations on documents, queries, bulk operations, and container management. Triggers: "Cosmos DB", "@azure/cosmos", "CosmosClient", "document CRUD", "NoSQL queries", "bulk operations", "partition key", "container.items".
package: "@azure/cosmos"
risk: unknown

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---
name: azure-data-tables-py
description: "|"
description: |
Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
Triggers: "table storage", "TableServiceClient", "TableClient", "entities", "PartitionKey", "RowKey".
package: azure-data-tables

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---
name: azure-eventgrid-dotnet
description: "|"
description: |
Azure Event Grid SDK for .NET. Client library for publishing and consuming events with Azure Event Grid. Use for event-driven architectures, pub/sub messaging, CloudEvents, and EventGridEvents. Triggers: "Event Grid", "EventGridPublisherClient", "CloudEvent", "EventGridEvent", "publish events .NET", "event-driven", "pub/sub".
package: Azure.Messaging.EventGrid
risk: unknown

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---
name: azure-eventgrid-py
description: "|"
description: |
Azure Event Grid SDK for Python. Use for publishing events, handling CloudEvents, and event-driven architectures.
Triggers: "event grid", "EventGridPublisherClient", "CloudEvent", "EventGridEvent", "publish events".
package: azure-eventgrid

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---
name: azure-eventhub-dotnet
description: "|"
description: |
Azure Event Hubs SDK for .NET. Use for high-throughput event streaming: sending events (EventHubProducerClient, EventHubBufferedProducerClient), receiving events (EventProcessorClient with checkpointing), partition management, and real-time data ingestion. Triggers: "Event Hubs", "event streaming", "EventHubProducerClient", "EventProcessorClient", "send events", "receive events", "checkpointing", "partition".
package: Azure.Messaging.EventHubs
risk: unknown

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---
name: azure-eventhub-py
description: "|"
description: |
Azure Event Hubs SDK for Python streaming. Use for high-throughput event ingestion, producers, consumers, and checkpointing.
Triggers: "event hubs", "EventHubProducerClient", "EventHubConsumerClient", "streaming", "partitions".
package: azure-eventhub

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---
name: azure-eventhub-rust
description: "|"
description: |
Azure Event Hubs SDK for Rust. Use for sending and receiving events, streaming data ingestion.
Triggers: "event hubs rust", "ProducerClient rust", "ConsumerClient rust", "send event rust", "streaming rust".
package: azure_messaging_eventhubs

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---
name: azure-identity-dotnet
description: "|"
description: |
Azure Identity SDK for .NET. Authentication library for Azure SDK clients using Microsoft Entra ID. Use for DefaultAzureCredential, managed identity, service principals, and developer credentials. Triggers: "Azure Identity", "DefaultAzureCredential", "ManagedIdentityCredential", "ClientSecretCredential", "authentication .NET", "Azure auth", "credential chain".
package: Azure.Identity
risk: unknown

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---
name: azure-identity-py
description: "|"
description: |
Azure Identity SDK for Python authentication. Use for DefaultAzureCredential, managed identity, service principals, and token caching.
Triggers: "azure-identity", "DefaultAzureCredential", "authentication", "managed identity", "service principal", "credential".
package: azure-identity

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---
name: azure-identity-rust
description: "|"
description: |
Azure Identity SDK for Rust authentication. Use for DeveloperToolsCredential, ManagedIdentityCredential, ClientSecretCredential, and token-based authentication.
Triggers: "azure-identity", "DeveloperToolsCredential", "authentication rust", "managed identity rust", "credential rust".
package: azure_identity

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---
name: azure-keyvault-certificates-rust
description: "|"
description: |
Azure Key Vault Certificates SDK for Rust. Use for creating, importing, and managing certificates.
Triggers: "keyvault certificates rust", "CertificateClient rust", "create certificate rust", "import certificate rust".
package: azure_security_keyvault_certificates

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---
name: azure-keyvault-keys-rust
description: "|"
description: |
Azure Key Vault Keys SDK for Rust. Use for creating, managing, and using cryptographic keys.
Triggers: "keyvault keys rust", "KeyClient rust", "create key rust", "encrypt rust", "sign rust".
package: azure_security_keyvault_keys

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---
name: azure-keyvault-py
description: "|"
description: |
Azure Key Vault SDK for Python. Use for secrets, keys, and certificates management with secure storage.
Triggers: "key vault", "SecretClient", "KeyClient", "CertificateClient", "secrets", "encryption keys".
package: azure-keyvault-secrets, azure-keyvault-keys, azure-keyvault-certificates

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---
name: azure-keyvault-secrets-rust
description: "|"
description: |
Azure Key Vault Secrets SDK for Rust. Use for storing and retrieving secrets, passwords, and API keys.
Triggers: "keyvault secrets rust", "SecretClient rust", "get secret rust", "set secret rust".
package: azure_security_keyvault_secrets

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---
name: azure-maps-search-dotnet
description: "|"
description: |
Azure Maps SDK for .NET. Location-based services including geocoding, routing, rendering, geolocation, and weather. Use for address search, directions, map tiles, IP geolocation, and weather data. Triggers: "Azure Maps", "MapsSearchClient", "MapsRoutingClient", "MapsRenderingClient", "geocoding .NET", "route directions", "map tiles", "geolocation".
package: Azure.Maps.Search
risk: unknown

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---
name: azure-messaging-webpubsubservice-py
description: "|"
description: |
Azure Web PubSub Service SDK for Python. Use for real-time messaging, WebSocket connections, and pub/sub patterns.
Triggers: "azure-messaging-webpubsubservice", "WebPubSubServiceClient", "real-time", "WebSocket", "pub/sub".
package: azure-messaging-webpubsubservice

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---
name: azure-mgmt-apicenter-dotnet
description: "|"
description: |
Azure API Center SDK for .NET. Centralized API inventory management with governance, versioning, and discovery. Use for creating API services, workspaces, APIs, versions, definitions, environments, deployments, and metadata schemas. Triggers: "API Center", "ApiCenterService", "ApiCenterWorkspace", "ApiCenterApi", "API inventory", "API governance", "API versioning", "API catalog", "API discovery".
package: Azure.ResourceManager.ApiCenter
risk: unknown

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---
name: azure-mgmt-apicenter-py
description: "|"
description: |
Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization.
Triggers: "azure-mgmt-apicenter", "ApiCenterMgmtClient", "API Center", "API inventory", "API governance".
package: azure-mgmt-apicenter

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---
name: azure-mgmt-apimanagement-dotnet
description: "|"
description: |
Azure Resource Manager SDK for API Management in .NET. Use for MANAGEMENT PLANE operations: creating/managing APIM services, APIs, products, subscriptions, policies, users, groups, gateways, and backends via Azure Resource Manager. Triggers: "API Management", "APIM service", "create APIM", "manage APIs", "ApiManagementServiceResource", "API policies", "APIM products", "APIM subscriptions".
package: Azure.ResourceManager.ApiManagement
risk: unknown

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---
name: azure-mgmt-apimanagement-py
description: "|"
description: |
Azure API Management SDK for Python. Use for managing APIM services, APIs, products, subscriptions, and policies.
Triggers: "azure-mgmt-apimanagement", "ApiManagementClient", "APIM", "API gateway", "API Management".
package: azure-mgmt-apimanagement

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---
name: azure-mgmt-applicationinsights-dotnet
description: "|"
description: |
Azure Application Insights SDK for .NET. Application performance monitoring and observability resource management. Use for creating Application Insights components, web tests, workbooks, analytics items, and API keys. Triggers: "Application Insights", "ApplicationInsights", "App Insights", "APM", "application monitoring", "web tests", "availability tests", "workbooks".
package: Azure.ResourceManager.ApplicationInsights
risk: unknown

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---
name: azure-mgmt-arizeaiobservabilityeval-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Arize AI Observability and Evaluation (.NET). Use when managing Arize AI organizations
on Azure via Azure Marketplace, creating/updating/deleting Arize resources, or integrating Arize ML observability
into .NET applications. Triggers: "Arize AI", "ML observability", "ArizeAIObservabilityEval", "Arize organization".

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---
name: azure-mgmt-botservice-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".
package: Azure.ResourceManager.BotService
risk: unknown

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---
name: azure-mgmt-botservice-py
description: "|"
description: |
Azure Bot Service Management SDK for Python. Use for creating, managing, and configuring Azure Bot Service resources.
Triggers: "azure-mgmt-botservice", "AzureBotService", "bot management", "conversational AI", "bot channels".
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-mgmt-fabric-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Fabric in .NET. Use for MANAGEMENT PLANE operations: provisioning, scaling, suspending/resuming Microsoft Fabric capacities, checking name availability, and listing SKUs via Azure Resource Manager. Triggers: "Fabric capacity", "create capacity", "suspend capacity", "resume capacity", "Fabric SKU", "provision Fabric", "ARM Fabric", "FabricCapacityResource".
package: Azure.ResourceManager.Fabric
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-mgmt-fabric-py
description: "|"
description: |
Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources.
Triggers: "azure-mgmt-fabric", "FabricMgmtClient", "Fabric capacity", "Microsoft Fabric", "Power BI capacity".
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-mgmt-weightsandbiases-dotnet
description: "|"
description: |
Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability. Triggers: "Weights and Biases", "W&B", "WeightsAndBiases", "ML experiment tracking", "model registry", "experiment management", "wandb".
package: Azure.ResourceManager.WeightsAndBiases
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-monitor-ingestion-java
description: "|"
description: |
Azure Monitor Ingestion SDK for Java. Send custom logs to Azure Monitor via Data Collection Rules (DCR) and Data Collection Endpoints (DCE).
Triggers: "LogsIngestionClient java", "azure monitor ingestion java", "custom logs java", "DCR java", "data collection rule java".
package: com.azure:azure-monitor-ingestion

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@@ -1,6 +1,6 @@
---
name: azure-monitor-ingestion-py
description: "|"
description: |
Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API.
Triggers: "azure-monitor-ingestion", "LogsIngestionClient", "custom logs", "DCR", "data collection rule", "Log Analytics".
package: azure-monitor-ingestion

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@@ -1,6 +1,6 @@
---
name: azure-monitor-opentelemetry-exporter-java
description: "|"
description: |
Azure Monitor OpenTelemetry Exporter for Java. Export OpenTelemetry traces, metrics, and logs to Azure Monitor/Application Insights.
Triggers: "AzureMonitorExporter java", "opentelemetry azure java", "application insights java otel", "azure monitor tracing java".
Note: This package is DEPRECATED. Migrate to azure-monitor-opentelemetry-autoconfigure.

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@@ -1,6 +1,6 @@
---
name: azure-monitor-opentelemetry-exporter-py
description: "|"
description: |
Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights.
Triggers: "azure-monitor-opentelemetry-exporter", "AzureMonitorTraceExporter", "AzureMonitorMetricExporter", "AzureMonitorLogExporter".
package: azure-monitor-opentelemetry-exporter

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@@ -1,6 +1,6 @@
---
name: azure-monitor-opentelemetry-py
description: "|"
description: |
Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.
Triggers: "azure-monitor-opentelemetry", "configure_azure_monitor", "Application Insights", "OpenTelemetry distro", "auto-instrumentation".
package: azure-monitor-opentelemetry

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@@ -1,6 +1,6 @@
---
name: azure-monitor-query-java
description: "|"
description: |
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
Triggers: "LogsQueryClient java", "MetricsQueryClient java", "kusto query java", "log analytics java", "azure monitor query java".
Note: This package is deprecated. Migrate to azure-monitor-query-logs and azure-monitor-query-metrics.

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@@ -1,6 +1,6 @@
---
name: azure-monitor-query-py
description: "|"
description: |
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
Triggers: "azure-monitor-query", "LogsQueryClient", "MetricsQueryClient", "Log Analytics", "Kusto queries", "Azure metrics".
package: azure-monitor-query

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@@ -1,6 +1,6 @@
---
name: azure-postgres-ts
description: "|"
description: |
Connect to Azure Database for PostgreSQL Flexible Server from Node.js/TypeScript using the pg (node-postgres) package. Use for PostgreSQL queries, connection pooling, transactions, and Microsoft Entra ID (passwordless) authentication. Triggers: "PostgreSQL", "postgres", "pg client", "node-postgres", "Azure PostgreSQL connection", "PostgreSQL TypeScript", "pg Pool", "passwordless postgres".
package: pg
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-resource-manager-cosmosdb-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Cosmos DB in .NET. Use for MANAGEMENT PLANE operations: creating/managing Cosmos DB accounts, databases, containers, throughput settings, and RBAC via Azure Resource Manager. NOT for data plane operations (CRUD on documents) - use Microsoft.Azure.Cosmos for that. Triggers: "Cosmos DB account", "create Cosmos account", "manage Cosmos resources", "ARM Cosmos", "CosmosDBAccountResource", "provision Cosmos DB".
package: Azure.ResourceManager.CosmosDB
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-resource-manager-durabletask-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Durable Task Scheduler in .NET. Use for MANAGEMENT PLANE operations: creating/managing Durable Task Schedulers, Task Hubs, and retention policies via Azure Resource Manager. Triggers: "Durable Task Scheduler", "create scheduler", "task hub", "DurableTaskSchedulerResource", "provision Durable Task", "orchestration scheduler".
package: Azure.ResourceManager.DurableTask
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-resource-manager-mysql-dotnet
description: "|"
description: |
Azure MySQL Flexible Server SDK for .NET. Database management for MySQL Flexible Server deployments. Use for creating servers, databases, firewall rules, configurations, backups, and high availability. Triggers: "MySQL", "MySqlFlexibleServer", "MySQL Flexible Server", "Azure Database for MySQL", "MySQL database management", "MySQL firewall", "MySQL backup".
package: Azure.ResourceManager.MySql
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-resource-manager-playwright-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Microsoft Playwright Testing in .NET. Use for MANAGEMENT PLANE operations: creating/managing Playwright Testing workspaces, checking name availability, and managing workspace quotas via Azure Resource Manager. NOT for running Playwright tests - use Azure.Developer.MicrosoftPlaywrightTesting.NUnit for that. Triggers: "Playwright workspace", "create Playwright Testing workspace", "manage Playwright resources", "ARM Playwright", "PlaywrightWorkspaceResource", "provision Playwright Testing".
package: Azure.ResourceManager.Playwright
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-resource-manager-postgresql-dotnet
description: "|"
description: |
Azure PostgreSQL Flexible Server SDK for .NET. Database management for PostgreSQL Flexible Server deployments. Use for creating servers, databases, firewall rules, configurations, backups, and high availability. Triggers: "PostgreSQL", "PostgreSqlFlexibleServer", "PostgreSQL Flexible Server", "Azure Database for PostgreSQL", "PostgreSQL database management", "PostgreSQL firewall", "PostgreSQL backup", "Postgres".
package: Azure.ResourceManager.PostgreSql
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-resource-manager-redis-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Redis in .NET. Use for MANAGEMENT PLANE operations: creating/managing Azure Cache for Redis instances, firewall rules, access keys, patch schedules, linked servers (geo-replication), and private endpoints via Azure Resource Manager. NOT for data plane operations (get/set keys, pub/sub) - use StackExchange.Redis for that. Triggers: "Redis cache", "create Redis", "manage Redis", "ARM Redis", "RedisResource", "provision Redis", "Azure Cache for Redis".
package: Azure.ResourceManager.Redis
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-resource-manager-sql-dotnet
description: "|"
description: |
Azure Resource Manager SDK for Azure SQL in .NET. Use for MANAGEMENT PLANE operations: creating/managing SQL servers, databases, elastic pools, firewall rules, and failover groups via Azure Resource Manager. NOT for data plane operations (executing queries) - use Microsoft.Data.SqlClient for that. Triggers: "SQL server", "create SQL database", "manage SQL resources", "ARM SQL", "SqlServerResource", "provision Azure SQL", "elastic pool", "firewall rule".
package: Azure.ResourceManager.Sql
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-search-documents-dotnet
description: "|"
description: |
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET", "SearchClient", "SearchIndexClient", "vector search C#", "semantic search .NET", "hybrid search", "Azure.Search.Documents".
package: Azure.Search.Documents
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-search-documents-py
description: "|"
description: |
Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.
Triggers: "azure-search-documents", "SearchClient", "SearchIndexClient", "vector search", "hybrid search", "semantic search".
package: azure-search-documents

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@@ -1,6 +1,6 @@
---
name: azure-security-keyvault-keys-dotnet
description: "|"
description: |
Azure Key Vault Keys SDK for .NET. Client library for managing cryptographic keys in Azure Key Vault and Managed HSM. Use for key creation, rotation, encryption, decryption, signing, and verification. Triggers: "Key Vault keys", "KeyClient", "CryptographyClient", "RSA key", "EC key", "encrypt decrypt .NET", "key rotation", "HSM".
package: Azure.Security.KeyVault.Keys
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-servicebus-dotnet
description: "|"
description: |
Azure Service Bus SDK for .NET. Enterprise messaging with queues, topics, subscriptions, and sessions. Use for reliable message delivery, pub/sub patterns, dead letter handling, and background processing. Triggers: "Service Bus", "ServiceBusClient", "ServiceBusSender", "ServiceBusReceiver", "ServiceBusProcessor", "message queue", "pub/sub .NET", "dead letter queue".
package: Azure.Messaging.ServiceBus
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-servicebus-py
description: "|"
description: |
Azure Service Bus SDK for Python messaging. Use for queues, topics, subscriptions, and enterprise messaging patterns.
Triggers: "service bus", "ServiceBusClient", "queue", "topic", "subscription", "message broker".
package: azure-servicebus

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@@ -1,6 +1,6 @@
---
name: azure-speech-to-text-rest-py
description: "|"
description: |
Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK.
Triggers: "speech to text REST", "short audio transcription", "speech recognition REST API", "STT REST", "recognize speech REST".
DO NOT USE FOR: Long audio (>60 seconds), real-time streaming, batch transcription, custom speech models, speech translation. Use Speech SDK or Batch Transcription API instead.

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@@ -1,6 +1,6 @@
---
name: azure-storage-blob-py
description: "|"
description: |
Azure Blob Storage SDK for Python. Use for uploading, downloading, listing blobs, managing containers, and blob lifecycle.
Triggers: "blob storage", "BlobServiceClient", "ContainerClient", "BlobClient", "upload blob", "download blob".
package: azure-storage-blob

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@@ -1,6 +1,6 @@
---
name: azure-storage-blob-rust
description: "|"
description: |
Azure Blob Storage SDK for Rust. Use for uploading, downloading, and managing blobs and containers.
Triggers: "blob storage rust", "BlobClient rust", "upload blob rust", "download blob rust", "container rust".
package: azure_storage_blob

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@@ -1,6 +1,6 @@
---
name: azure-storage-blob-ts
description: "|"
description: |
Azure Blob Storage JavaScript/TypeScript SDK (@azure/storage-blob) for blob operations. Use for uploading, downloading, listing, and managing blobs and containers. Supports block blobs, append blobs, page blobs, SAS tokens, and streaming. Triggers: "blob storage", "@azure/storage-blob", "BlobServiceClient", "ContainerClient", "upload blob", "download blob", "SAS token", "block blob".
package: "@azure/storage-blob"
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-storage-file-datalake-py
description: "|"
description: |
Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations.
Triggers: "data lake", "DataLakeServiceClient", "FileSystemClient", "ADLS Gen2", "hierarchical namespace".
package: azure-storage-file-datalake

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@@ -1,6 +1,6 @@
---
name: azure-storage-file-share-py
description: "|"
description: |
Azure Storage File Share SDK for Python. Use for SMB file shares, directories, and file operations in the cloud.
Triggers: "azure-storage-file-share", "ShareServiceClient", "ShareClient", "file share", "SMB".
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-storage-file-share-ts
description: "|"
description: |
Azure File Share JavaScript/TypeScript SDK (@azure/storage-file-share) for SMB file share operations. Use for creating shares, managing directories, uploading/downloading files, and handling file metadata. Supports Azure Files SMB protocol scenarios. Triggers: "file share", "@azure/storage-file-share", "ShareServiceClient", "ShareClient", "SMB", "Azure Files".
package: "@azure/storage-file-share"
risk: unknown

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@@ -1,6 +1,6 @@
---
name: azure-storage-queue-py
description: "|"
description: |
Azure Queue Storage SDK for Python. Use for reliable message queuing, task distribution, and asynchronous processing.
Triggers: "queue storage", "QueueServiceClient", "QueueClient", "message queue", "dequeue".
package: azure-storage-queue

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@@ -1,6 +1,6 @@
---
name: azure-storage-queue-ts
description: "|"
description: |
Azure Queue Storage JavaScript/TypeScript SDK (@azure/storage-queue) for message queue operations. Use for sending, receiving, peeking, and deleting messages in queues. Supports visibility timeout, message encoding, and batch operations. Triggers: "queue storage", "@azure/storage-queue", "QueueServiceClient", "QueueClient", "send message", "receive message", "dequeue", "visibility timeout".
package: "@azure/storage-queue"
risk: unknown

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@@ -1,6 +1,7 @@
---
name: backend-architect
description: "Expert backend architect specializing in scalable API design,"
description: |
Expert backend architect specializing in scalable API design,
microservices architecture, and distributed systems. Masters REST/GraphQL/gRPC
APIs, event-driven architectures, service mesh patterns, and modern backend
frameworks. Handles service boundary definition, inter-service communication,

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@@ -1,6 +1,7 @@
---
name: backend-security-coder
description: "Expert in secure backend coding practices specializing in input"
description: |
Expert in secure backend coding practices specializing in input
validation, authentication, and API security. Use PROACTIVELY for backend
security implementations or security code reviews.
metadata:

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@@ -1,6 +1,7 @@
---
name: bash-pro
description: "Master of defensive Bash scripting for production automation, CI/CD"
description: |
Master of defensive Bash scripting for production automation, CI/CD
pipelines, and system utilities. Expert in safe, portable, and testable shell
scripts.
metadata:

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@@ -1,6 +1,7 @@
---
name: blockchain-developer
description: "Build production-ready Web3 applications, smart contracts, and"
description: |
Build production-ready Web3 applications, smart contracts, and
decentralized systems. Implements DeFi protocols, NFT platforms, DAOs, and
enterprise blockchain integrations. Use PROACTIVELY for smart contracts, Web3
apps, DeFi protocols, or blockchain infrastructure.

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@@ -1,6 +1,7 @@
---
name: business-analyst
description: "Master modern business analysis with AI-powered analytics,"
description: |
Master modern business analysis with AI-powered analytics,
real-time dashboards, and data-driven insights. Build comprehensive KPI
frameworks, predictive models, and strategic recommendations. Use PROACTIVELY
for business intelligence or strategic analysis.

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@@ -1,6 +1,7 @@
---
name: c4-code
description: "Expert C4 Code-level documentation specialist. Analyzes code"
description: |
Expert C4 Code-level documentation specialist. Analyzes code
directories to create comprehensive C4 code-level documentation including
function signatures, arguments, dependencies, and code structure. Use when
documenting code at the lowest C4 level for individual directories and code

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@@ -1,6 +1,7 @@
---
name: c4-component
description: "Expert C4 Component-level documentation specialist. Synthesizes C4"
description: |
Expert C4 Component-level documentation specialist. Synthesizes C4
Code-level documentation into Component-level architecture, defining component
boundaries, interfaces, and relationships. Creates component diagrams and
documentation. Use when synthesizing code-level documentation into logical

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@@ -1,6 +1,7 @@
---
name: c4-container
description: "Expert C4 Container-level documentation specialist. Synthesizes"
description: |
Expert C4 Container-level documentation specialist. Synthesizes
Component-level documentation into Container-level architecture, mapping
components to deployment units, documenting container interfaces as APIs, and
creating container diagrams. Use when synthesizing components into deployment

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@@ -1,6 +1,7 @@
---
name: c4-context
description: "Expert C4 Context-level documentation specialist. Creates"
description: |
Expert C4 Context-level documentation specialist. Creates
high-level system context diagrams, documents personas, user journeys, system
features, and external dependencies. Synthesizes container and component
documentation with system documentation to create comprehensive context-level

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@@ -1,6 +1,7 @@
---
name: cloud-architect
description: "Expert cloud architect specializing in AWS/Azure/GCP multi-cloud"
description: |
Expert cloud architect specializing in AWS/Azure/GCP multi-cloud
infrastructure design, advanced IaC (Terraform/OpenTofu/CDK), FinOps cost
optimization, and modern architectural patterns. Masters serverless,
microservices, security, compliance, and disaster recovery. Use PROACTIVELY

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@@ -1,6 +1,7 @@
---
name: competitive-landscape
description: "This skill should be used when the user asks to \\\"analyze"
description: |
This skill should be used when the user asks to \\\"analyze
competitors", "assess competitive landscape", "identify differentiation",
"evaluate market positioning", "apply Porter's Five Forces", or requests
competitive strategy analysis.

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@@ -1,6 +1,7 @@
---
name: conductor-setup
description: "Initialize project with Conductor artifacts (product definition,"
description: |
Initialize project with Conductor artifacts (product definition,
tech stack, workflow, style guides)
metadata:
argument-hint: "[--resume]"

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@@ -1,6 +1,7 @@
---
name: conductor-validator
description: "Validates Conductor project artifacts for completeness,"
description: |
Validates Conductor project artifacts for completeness,
consistency, and correctness. Use after setup, when diagnosing issues, or
before implementation to verify project context.
allowed-tools: Read Glob Grep Bash

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@@ -1,6 +1,7 @@
---
name: content-marketer
description: "Elite content marketing strategist specializing in AI-powered"
description: |
Elite content marketing strategist specializing in AI-powered
content creation, omnichannel distribution, SEO optimization, and data-driven
performance marketing. Masters modern content tools, social media automation,
and conversion optimization with 2024/2025 best practices. Use PROACTIVELY for

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@@ -1,6 +1,7 @@
---
name: context-driven-development
description: "Use this skill when working with Conductor's context-driven"
description: |
Use this skill when working with Conductor's context-driven
development methodology, managing project context artifacts, or understanding
the relationship between product.md, tech-stack.md, and workflow.md files.
metadata:

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