'conversations' 검색 결과

Load company background for executive advisor sessions, check whether it is outdated or incomplete, and propose updates learned during conversations. Apply rules for excluding sensitive details and anonymizing permitted information before external searches or API calls.

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• Loading company background before an executive advisor session
• Checking outdated or incomplete company information
• Proposing context updates from new conversation details

Turn selected research conversations or notes into themes supported by evidence and counterexamples. Distinguish observed behavior from preferences and hypotheses, assess confidence, and suggest a small next experiment with an observable measure of success.

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• Finding recurring themes across research interviews
• Comparing evidence, counterexamples, and confidence
• Planning a small experiment to test findings

Build conversations and workflows with the Gemini Interactions API on Gemini Enterprise Agent Platform. Follow Python or JavaScript examples for server-stored conversation history, streaming responses, structured JSON output, function calls, and background agent tasks.

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• Building chats that retain conversation context
• Displaying responses as they stream
• Returning JSON in a specified format

Create and manage custom Agent resources on Gemini Enterprise Agent Platform before running conversations. Prepare REST requests to configure instructions, attach files and skills, connect tools, track creation progress, and retrieve, update, or delete agents.

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• Create an Agent with task-specific instructions
• Attach files and skills from Cloud Storage or Skill Registry
• Configure connections to external MCP tools

Connect Kortix to Microsoft Teams and handle conversations with progress updates, final replies, and interactive questions. The skill also covers reading channel discussions, exchanging files, and posting to conversations the bot has already joined.

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• Connect Kortix to Microsoft Teams
• Show task progress and deliver a final reply
• Receive attachments and share completed files

Diagnose why an AI agent becomes less reliable as conversations and documents accumulate. Distinguish missed information, persistent false claims, irrelevant material, mixed tasks, and conflicting sources, then choose ways to clean, reorganize, or separate the context.

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• Investigating declining quality in long conversations
• Recovering from false claims that persist after correction
• Resolving conflicts between retrieved documents

Turn OpenClaw conversations, actions, and tool history into structured long-term memory. Agents can retrieve past facts, decisions, and summaries when needed, helping them continue work across sessions and recover context after it is shortened.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Retrieve decisions made in previous sessions
• Review summaries of earlier work
• Recover context after conversation compaction

Analyze meeting transcripts to understand speaking habits, interruptions, conflict avoidance, and listening patterns. Get specific examples with timestamps and practical suggestions, then compare meetings over time to track changes in communication and facilitation.

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• Find moments when difficult conversations were avoided
• Review speaking time and interruptions
• Assess facilitation in team meetings

Build LLM serving workflows that produce JSON or other required formats. The skill covers reusing computation for shared prompts, tool calls, and ongoing conversations, with examples for server setup and structured output.

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• Extracting article details into JSON
• Building agents that call tools
• Reusing shared prompts across conversations

Reviews recent changes, CI failures, open issues, pull requests, and conversations to produce a prioritized findings report. It separates urgent work from monitoring and noise, suggests next actions, and records facts for the next automated review cycle.

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• Prioritizing recent CI and test failures
• Reviewing blocked pull requests and unanswered issues
• Preparing next actions for an automated work cycle

Review recent changes, automated test failures, issues, and conversations to prioritize engineering work. Produce a concise report separating urgent actions, watch items, noise, and state updates, with suggested next steps and rough effort estimates.

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• Prioritizing recent CI and test failures
• Sorting team issues and conversation findings
• Separating urgent work from items to monitor

Manage an AI agent’s presence on Moltbook, a social network for agents. The skill covers registration, posts, comments, votes, community creation, and finding relevant conversations through search that matches meaning rather than exact words.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Register an agent and set up its profile
• Share discoveries and reply to comments
• Find conversations about a topic

Plan stakeholder conversations before retiring a product or feature. Get an ordered sequence of meetings, with questions, commitments, warning signs, and required outcomes, adjusted to the scale and complexity of the retirement.

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• Planning conversations before a product retirement
• Checking promises made by Sales before announcing
• Coordinating a retirement involving resellers

Design a content marketing system that connects posts, videos, and newsletters to sales opportunities. It helps analyze successful content, adapt one core piece for multiple platforms, plan follow-up conversations, and measure which content contributes to deals.

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• Plan a content workflow within a weekly time budget
• Adapt one article or video for multiple platforms
• Connect newsletters and engaged readers to sales conversations

Build third-party tools to inspect, extract, migrate, or analyze DeepChat's local settings and conversations. Work through data locations, database encryption, and table relationships while favoring read-only copies and redacted output.

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• Building an importer for another application
• Inspecting provider, model, and MCP settings
• Extracting conversations for analysis

Set up and operate Proactive Agent to organize project progress across conversations and suggest next steps in a web workspace. Accepted suggestions return through a connector to the original session for continued work.

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• Track project progress across multiple conversations
• Review suggested next steps in a web workspace
• Continue accepted tasks in the original session

Extract lessons from corrections, praise, and unexpected cases in conversations. Organize findings by confidence level and propose updates to individual agent histories or shared team decisions, with changes shown for approval before saving.

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• Capture lessons after correcting an agent
• Record successful output formats
• Consolidate lessons at the end of a session

Track author replies to your LinkedIn comments and organize conversations by elapsed time. Receive a report of reply status and recommended actions, with follow-up drafting routed to a related skill for timely responses.

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• Review conversations needing follow-up today
• Check replies after posting several comments
• Prepare a response to a post author's reply

Build AI chat screens in React with @ant-design/x. This skill guides component selection, API usage, and page composition for message bubbles, input boxes, conversation lists, attachments, source references, and other chat interface elements.

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• Build a chat screen with message bubbles and an input box
• Add conversation lists and switching
• Display attachments and source references

Build AI chat interfaces with @ant-design/x, a React library of interface components. Get guidance on choosing and combining message bubbles, input boxes, conversation lists, attachments, and source citations, with API references and common implementation pitfalls.

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• Build a chat page with message bubbles and an input box
• Add a conversation list and switching controls
• Display attachments and source citations

Implement AI chat behavior with useXChat, a React function for managing chat state. Connect Providers that handle API communication, manage messages and errors, regenerate or cancel replies, and support multiple conversations with separate state.

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• Connect chat messages to Bubble.List and Sender
• Handle network errors and canceled replies
• Add message deletion and reply regeneration

Implement AI chat behavior with useXChat, a React function for managing chat state. Connect Providers that handle API communication, manage messages and errors, regenerate or cancel replies, and support multiple conversations with separate state.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connect chat messages to Bubble.List and Sender
• Handle network errors and canceled replies
• Add message deletion and reply regeneration

Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Structured approach to workplace conflicts, performance discussions, and challenging feedback using preparation-delivery-followup framework. Use when preparing for tough conversations, addressing conflicts, giving critical feedback, or navigating sensitive workplace discussions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.