Results for “conversation”

Design a new PM skill through guided conversation, from raw idea to a structured, repo-compliant SKILL.md draft.

Add real-time voice conversations to a custom agent runtime using ElevenLabs Speech Engine, handling WebSocket servers, browser clients, and interruption-aware streaming.

Build multi-agent conversation systems with AutoGen, including two-agent chats, group chats, function calling, and nested conversations with code execution and human-in-the-loop options.

Capture idea or task as todo from current conversation context

Complete WhatsApp management for OpenClaw agents: per-conversation memory (groups + DMs), unanswered message tracking, loop prevention, and multi-PA coordination. Use when: tracking conversation context, recalling past decisions, finding unanswered messages, or preventing echo/duplicate message loops.

Search and analyze your own session logs (older/parent conversations) using jq.

Expert en optimisation recherche vocale (structured data, featured snippets, queries conversationnelles)

Search and analyze your own session logs (older/parent conversations) using jq.

Search and analyze your own session logs (older/parent conversations) using jq.

Compact the current conversation into a handoff document for another agent to pick up.

Framework for building multi-agent conversation systems with customizable LLM-powered agents

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document for another agent to pick up.

Search and analyze your own session logs (older/parent conversations) using jq.

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document for another agent to pick up.

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

Automates X (Twitter) DM workflows: scan inbox, read conversations, generate persona-based replies, and send messages. Also supports searching users and starting new conversations with rate control and E2E passcode unlock.

Orchestrates group discussions between installed BMAD agents, enabling natural multi-agent conversations where each agent is a real subagent with independent thinking. Use when user requests party mode, wants multiple agent perspectives, group discussion, roundtable, or multi-agent conversation about their project.

Compact the current conversation into a handoff document for another agent to pick up.

Compact the current conversation into a handoff document for another agent to pick up.

Create a slide-by-slide roadmap review structure for planning and leadership conversations.

Creates multi-agent AI systems with AutoGen, enabling agent conversations, tool use, and group chats.

Compact the current conversation into a handoff document for another agent to pick up.

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK, with support for function tools, hosted tools, MCP servers, conversation threads, and streaming responses.

Search past WhatsApp/chat conversations stored in the audit log PostgreSQL database. Use when the user asks about past conversations, what was discussed, what someone said, finding a specific message, or referencing previous discussions. Also use to reply to or quote specific past messages.

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Hand the current conversation off to a fresh background agent that picks up the work immediately.

Use to audit arrears, collections and financial-difficulty conversations for fair treatment — forbearance offered, pressure absent, vulnerability recognised. Trigger for "audit our collections calls", "are we treating customers in arrears fairly", "did we offer forbearance", financial difficulty handling, payment plan conversations, or a complaint about collections conduct.