'llm-apps' 검색 결과

Investigate why a file or function exists using local Git history. Trace its introduction, later edits, authorship, and files often changed alongside it, then summarize likely intent and change risks while distinguishing evidence from inference.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understanding why an unfamiliar function exists
• Reviewing historical constraints before a refactor
• Tracing the background of a workaround

Inspect Python and JavaScript dependency files for missing version constraints, duplicate entries, conflicting exact versions, and outdated Python compatibility packages. Get plain-language explanations and focused repair suggestions, with offline checks by default.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check dependency files before investigating installation failures
• Find outdated Python compatibility packages
• Review duplicate entries and conflicting exact versions

Build MCP servers that let AI access actions and data using mcp-use. The guide covers project setup, reusable prompts, interactive React interfaces, authentication, error handling, and deployment, with reference files for each area.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create a new MCP server with mcp-use
• Add actions, data resources, or reusable prompts
• Build interactive React interfaces for browsing and selection

Coordinate large research or generation tasks across a model team. An orchestrator plans and checks the work, workers execute subtasks in parallel, and an advisor reviews the plan and draft before the results are combined.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Research multiple competitors in parallel
• Split a large generation task across multiple models
• Have an advisor review plans and drafts

Develop ChatGPT apps with interactive React widgets using mcp-use and OpenAI Apps SDK. Guidance covers app scope, server tools, shared state, and display settings. This skill is deprecated and points users to mcp-app-builder.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Define the scope of a ChatGPT app
• Build React widgets connected to server tools
• Share widget state with ChatGPT

Turn rambling messages or voice dictation into a structured brief covering goals, decisions, open questions, reversals, and parked ideas. Separate the agent’s assumptions from the user’s statements and confirm understanding before work begins.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Organize ideas captured through voice dictation
• Confirm requirements before starting work
• Collect thoughts across multiple messages

Compare a Git diff with its stated purpose to flag potentially unrelated files, added dependencies, API renames, and configuration changes. Receive recommendations to keep, split, or justify changes, with a proposed grouping for follow-up work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check scope before opening a pull request
• Find unexpected changes in a bug fix
• Review whether staged changes are too broad

Simulate readers encountering a draft for the first time to see whether they open it, where their attention fades, and what they remember. Receive reader comments alongside the text without rewrites or suggested fixes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check whether a post earns a full read
• Find where readers lose interest
• Compare reader reactions after revisions

A deprecated guide to building MCP servers with mcp-use, covering callable actions, data resources, reusable prompts, and interactive widgets. It includes design references and code examples, and directs users to the replacement skill, mcp-app-builder.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review the structure of an existing mcp-use server
• Consult examples of tools, resources, and prompts
• Explore interactive widget design

Review abandoned personal projects through local Git history to identify likely stopping points and recurring patterns. Compare revival candidates, select one worth revisiting, and outline concrete steps from checking whether it still runs to publishing it.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Taking stock of unfinished personal projects
• Finding recurring reasons projects stall
• Choosing one project to revive and publish

Dify is an open-source platform for building LLM apps such as chatbots, agents, workflows and RAG knowledge bases, and it exposes every published app as a REST API. Use when a user asks to self-host Dify with Docker Compose, configure Dify environment variables, call a Dify app or workflow API, upload documents to a Dify knowledge base, export or import a Dify DSL file, run a Dify app from the terminal with difyctl, or upgrade and back up a Dify instance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.