Results for “beyond-semantic-speech”

12 skills
More results
github
Semantic Kernel
Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.
36.2k · bundle
elevenlabs
Text To Speech
Generate natural speech from text using ElevenLabs voice AI, supporting 70+ languages, multiple models, and various output formats.
363 · bundle
orchestra-research
Sentence Transformers
Generate high-quality sentence and text embeddings for semantic similarity, clustering, and retrieval using 5000+ pre-trained models. Supports multilingual and domain-specific embeddings for RAG and semantic search.
10.4k · bundle
qcmuu
Sentence Transformers
Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.
0 · bundle
pablolion
Bmad Advanced Elicitation
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
12 · bundle
comeonoliver
Speech
Generates spoken audio clips from text for narration, voiceovers, IVR prompts, and accessibility reads, with support for single clips and batch processing.
61
delorenj
Bmad Advanced Elicitation
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
1 · bundle
inference-sh
Text To Speech
Convert text to natural speech using multiple TTS models via the inference.sh CLI, with support for emotion steering, voice cloning, and multi-speaker dialogue.
584
dokhacgiakhoa
Brainstorming
Socratic questioning protocol + user communication.
505 · bundle
shulkwisec
AI Prompt Leaking
Systematically extract hidden system prompts, core directives, and invisible context intentionally concealed within Large Language Model (LLM) applications. This skill utilizes targeted linguistic engineering and boundary manipulation to bypass prompt opacity.
21 · bundle
michaelschecht
Causal Inference
Frame causal questions and estimate treatment effects with assumption checks. Use when: (1) policy impact analysis, (2) A/B interpretation beyond correlation, (3) confounding diagnostics. NOT for: medical/legal conclusions without experts.
0