“natural-language”的搜索结果

帮助在现有Web应用中嵌入可通过自然语言操作界面的AI助手，涵盖安装、显示操作面板、连接LLM、验证交互，以及正式上线时保护API密钥的配置。

• 用文字操作业务界面
• 为现有Web应用嵌入AI助手
• 在真实界面中制作产品演示

Describe browser actions in everyday language and let page-agent carry them out. Useful when page elements are hard to identify reliably, with a fallback to direct element-based browser tools if the natural-language setup is unavailable.

中文简介正在准备中。当前显示英语简介。

• Clicking a button described in everyday language
• Entering a search term and submitting the form
• Interacting with pages whose element identifiers change

Build command-line interfaces for graphical applications in Cursor using the CLI-Anything workflow. It supports creating and extending these interfaces, running tests, checking required criteria, and listing tools through slash commands or natural-language requests.

中文简介正在准备中。当前显示英语简介。

• Build a command-line interface for a graphical application
• Extend an existing CLI to cover more operations
• Run tests and validate a CLI implementation

Use natural-language requests with Aomi CLI to check crypto prices and balances or prepare swaps, staking, and transfers between chains. Review queued transactions and simulate multi-step batches before separately authorizing wallet signing.

中文简介正在准备中。当前显示英语简介。

• Check crypto prices and wallet balances
• Prepare and simulate a Uniswap swap
• Prepare an ETH stake with Lido

Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, Graph_Render_View, Graph_Fold_By_Property, IRQL graph enrichment, graph mapping for existing query results, icon-decorated graph, fold graph nodes. Use azure-kusto-graph for native make-graph analysis, graph-match, shortest paths, components, or persistent graphs.

中文简介正在准备中。当前显示原文说明。

Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, Graph_Render_View, Graph_Fold_By_Property, IRQL graph enrichment, graph mapping for existing query results, icon-decorated graph, fold graph nodes. Use azure-kusto-graph for native make-graph analysis, graph-match, shortest paths, components, or persistent graphs.

中文简介正在准备中。当前显示原文说明。

Goal-driven E2E testing where a browser agent (Playwright MCP / computer-use) reads a natural-language goal and explores the app via the accessibility tree to assert outcomes — no pre-written script. Covers when intent-driven beats scripted, making agent runs deterministic (pinned model, temperature 0, seeded data, bounded steps, explicit success assertion, snapshot-not-pixel), cost/latency control, the accessibility-tree-first interaction model, CI gating, and graduating a stable run into a scripted Playwright test. Use when: "agentic browser test," "goal-driven browser test," "let an agent explore the app," "natural-language E2E," "browser agent smoke test," "Playwright MCP test." Not for: Writing/maintaining deterministic scripted Playwright tests — that is playwright-automation. Testing your product's OWN LLM features — that is ai-system-testing. Related: playwright-automation, ai-system-testing, exploratory-testing, test-reliability, qa-project-context.

中文简介正在准备中。当前显示原文说明。

Craft high-quality natural-language image prompts for any modern text-to-image or image-edit model that accepts flowing English. Trigger when the user wants help writing, rewriting, improving, or translating an English natural-language image prompt — including "write me an image prompt", "improve this image prompt", "describe this scene for an image model", or "convert these tags into a natural language prompt". Do NOT trigger for requests that are purely about dispatching to an image API, choosing samplers/schedulers, picking LoRAs, or setting up ControlNet — those belong to a runtime skill.

中文简介正在准备中。当前显示原文说明。

通过自然语言指令，使用nano-pdf修改PDF的指定页面，可更换标题或修正副标题中的错字。编辑后检查目标页面和输出内容。

• 更改PDF页面标题
• 修正PDF副标题中的错字
• 一次提出标题更改和错字修正

Generate short videos with audio from prompts and reference images, then refine them through conversational edits. The skill covers targeted object, lighting, and text changes, plus timed actions, using Gemini Omni Flash through documented video tools.

中文简介正在准备中。当前显示英语简介。

• Creating short videos with sound from written prompts
• Assigning reference images to characters, products, or styles
• Refining objects, lighting, and text through conversation

Use natural language to compare Binance P2P offers, prices, and payment methods. Review personal orders and dispute progress, submit evidence for existing appeals, and manage advertisements when the account has the required merchant permissions.

中文简介正在准备中。当前显示英语简介。

• Compare P2P offers by payment method
• Review personal order history and details
• Track appeals and submit supporting evidence

Find and evaluate a small, compatible set of AI Agent Skills for a multi-step goal. Check existing capabilities, compare candidates for fit and safety, identify overlaps, and prepare recommendations with installation subject to user approval.

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• Choose a set of Skills for a multi-step project
• Audit installed Skills for overlap and conflicts
• Find supporting Skills for writing quality or compliance

Search financial news, industry developments, and company sentiment using natural-language questions. Retrieve related headlines, summaries, sources, and article links through a Python script, with optional date ranges to focus the search on a specific period.

中文简介正在准备中。当前显示英语简介。

• Finding financial news related to a question
• Researching market and industry developments
• Checking news and public sentiment about a company

Turn a plain-language data request into SQL tailored to your database. Build queries that combine tables, filter records, and calculate summaries, with explanations of each step, performance considerations, and suggestions for adjusting dates or other conditions.

中文简介正在准备中。当前显示英语简介。

• Create SQL for order counts by status
• Analyze retention by signup month
• Query large tables with date-based partitions

Turn a written app specification into a runnable starter project using the requested technology stack. Generate implemented features, tests, configuration files, and setup instructions, then check the project for common omissions.

中文简介正在准备中。当前显示英语简介。

• Turning a requirements document into a starter project
• Creating a task API with FastAPI and SQLite
• Building a recipe-sharing website with Next.js

Manage Linear issues and projects through natural-language requests. Review priorities, create and update tickets, inspect team workloads, and organize release plans using a workflow that reads existing information before making changes.

中文简介正在准备中。当前显示英语简介。

• Prioritize bugs by their impact on users
• Plan issues and assignments for the next sprint
• Review workloads and redistribute assignments

Review articles, emails, documentation, and other reader-facing prose for invisible characters and formulaic writing. When measured signals are high, revise the wording while preserving facts, the writer’s voice, code, citations, and required disclosures.

中文简介正在准备中。当前显示英语简介。

• Final checks on articles and manuscripts
• Polishing emails and product copy
• Reviewing prose in Markdown and HTML

Manage Linear issues and projects through natural-language requests. Review priorities, create and update tickets, inspect team workloads, and organize release plans using a workflow that reads existing information before making changes.

中文简介正在准备中。当前显示英语简介。

• Prioritize bugs by their impact on users
• Plan issues and assignments for the next sprint
• Review workloads and redistribute assignments

Turn a written traffic situation into a Scenic file, which describes possible scenes using placement rules and constraints. Select suitable maps and actors, then check that the file compiles and can generate at least one scene.

中文简介正在准备中。当前显示英语简介。

• Create a scenario with a car cutting in from the right
• Describe a pedestrian crossing ahead of the main vehicle
• Build an unsignalized intersection scenario

Control CARLA’s on-screen camera to view a vehicle from behind, above, the driver’s seat, or the front. Select vehicles by name, role, or ID, frame them once, or follow them as they move.

中文简介正在准备中。当前显示英语简介。

• Following the ego vehicle from behind
• Viewing a Toyota Prius from the driver’s seat
• Watching a vehicle from above

Change weather on a running CARLA simulation server using requests such as heavy rain at sunset or a foggy night. The skill maps words to presets or exact parameters, applies them, and reads back the resulting settings.

中文简介正在准备中。当前显示英语简介。

• Setting heavy rain at sunset
• Creating a calm, foggy night scene
• Adjusting only the sun's height

Explore roads, lanes, and junctions in a CARLA simulation map through text reports and visual overlays. Locate places described in everyday language, inspect nearby lane details, and trace a path forward or backward along a lane.

中文简介正在准备中。当前显示英语简介。

• Understand a map's road and lane layout
• Compare the road network overlay with visible roads
• Locate the four-way junction nearest the map center

Guides image classification and search with OpenAI's CLIP by comparing images with text descriptions, without additional training. Includes batch processing, image-text matching, and category-based checks for potentially inappropriate images.

中文简介正在准备中。当前显示英语简介。

• Classify images using text labels without additional training
• Search an image collection with natural-language descriptions
• Compare how closely images match text descriptions

Build evaluation suites for AI features with the Axiom AI SDK. Generate test files, scoring functions, test cases, and configurable parameters from descriptions and existing code to compare changes and monitor output quality in production.

中文简介正在准备中。当前显示英语简介。

• Add regression evaluations for an AI feature
• Score classification, retrieval, and structured outputs
• Compare model and parameter configurations