audio-language-models
Gemini Live API, Grok Voice Agent, GPT-4o-Transcribe, AssemblyAI patterns for real-time voice, speech-to-text, and TTS. Use when implementing voice agents, audio transcription, or conversational AI.
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Gemini Live API, Grok Voice Agent, GPT-4o-Transcribe, AssemblyAI patterns for real-time voice, speech-to-text, and TTS. Use when implementing voice agents, audio transcription, or conversational AI.
Text embeddings for semantic search and similarity. Use when converting text to vectors, choosing embedding models, implementing chunking strategies, or building document similarity features.
GPT-5/4o, Claude 4.5, Gemini 2.5/3, Grok 4 vision patterns for image analysis, document understanding, and visual QA. Use when implementing image captioning, document/chart analysis, or multi-image comparison.
Search and retrieve decisions and patterns from knowledge graph. Use when recalling patterns, retrieving memories, finding past decisions.
LLM guardrails with NeMo, Guardrails AI, and OpenAI. Input/output rails, hallucination prevention, fact-checking, toxicity detection, red-teaming patterns. Use when building LLM guardrails, safety checks, or re...
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
LLM output evaluation and quality assessment. Use when implementing LLM-as-judge patterns, quality gates for AI outputs, or automated evaluation pipelines.
Reranking patterns for improving search precision. Use when implementing cross-encoder reranking, LLM-based relevance scoring, or improving retrieval quality in RAG pipelines.
HyDE (Hypothetical Document Embeddings) for improved semantic retrieval. Use when queries don't match document vocabulary, retrieval quality is poor, or implementing advanced RAG patterns.
Query decomposition for multi-concept retrieval. Use when handling complex queries spanning multiple topics, implementing multi-hop retrieval, or improving coverage for compound questions.
Redis semantic caching for LLM applications. Use when implementing vector similarity caching, optimizing LLM costs through cached responses, or building multi-level cache hierarchies.
Configure ReinforceNow training runs with config.yml and train.jsonl. Also covers converting HuggingFace datasets to ReinforceNow format. Triggers on "config.yml", "train.jsonl", "training config", "batch_size"...
Store decisions and patterns in knowledge graph with optional cloud sync. Use when saving patterns, storing decisions, remembering approaches that worked.
Comprehensive API design patterns for REST, GraphQL, and gRPC. Use when designing APIs, creating endpoints, adding routes, implementing pagination, rate limiting, or authentication patterns.
LangGraph human-in-the-loop patterns. Use when implementing approval workflows, manual review gates, user feedback integration, or interactive agent supervision.
Error pattern analysis and troubleshooting for Claude Code sessions. Use when handling errors, fixing failures, troubleshooting issues.
Use this skill when creating or evolving design systems for applications. Provides design token structures, component architecture patterns, documentation templates, and accessibility guidelines. Ensures consis...
Analyze, evolve, and rollback skills based on usage patterns. Use when evolving skills, improving skill definitions, updating skill content.
Manage the SkillForge feedback system that learns from your usage. Use when providing feedback, reporting issues, suggesting improvements.
Deep codebase exploration with parallel specialized agents. Use when exploring a repo, finding files, or discovering architecture with the explore agent.
Multi-agent coordination and synthesis patterns. Use when orchestrating multiple specialized agents, implementing fan-out/fan-in workflows, or synthesizing outputs from parallel agents.
Use this skill when documenting significant architectural decisions. Provides ADR templates following the Nygard format with sections for context, decision, consequences, and alternatives. Use when writing ADRs...
Production-grade fault tolerance for distributed systems. Use when implementing circuit breakers, retry with exponential backoff, bulkhead isolation patterns, or building resilience into LLM API integrations.
Format train.jsonl training data for ReinforceNow. Use when creating train.jsonl, formatting training entries, using tools/rewards per entry, or setting up sandbox/docker. Triggers on "train.jsonl", "training d...
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