“end-to-end”的搜索结果

从设计或需求文档中规划可完整运行的小功能单元，依次完成初始框架搭建、生成与评估迭代、审查及审批，组装可运行的最小可行产品，并分别提交框架与各项功能。

• 根据设计文档构建可运行的MVP
• 规划端到端运行的小功能单元
• 搭建首个可运行功能的初始框架

Create, update, and debug Docker-based end-to-end tests for the Composio CLI. Covers running the executable, keeping test data separate, checking command output, and maintaining package manifests within the CLI test suite.

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• Add end-to-end tests for CLI commands
• Debug unexpected CLI test output
• Keep test data isolated between tests

Run NemoClaw live end-to-end tests, which check complete workflows, or inspect existing release evidence. Routes requests to local or trusted GitHub workflows and reports the tested commit, results, workflow link, and relevant job links.

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• Run end-to-end tests for the latest pull request commit
• Run end-to-end tests for the current main commit
• Test working-tree source in a requested local run

Build end-to-end tests that follow user journeys in browsers and mobile simulators or emulators. Guides e2e configuration, AI-driven actions, precise outcome checks, failure investigation, and exploratory bug hunts backed by reproducible tests.

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• Testing browser user journeys with AI-driven actions
• Checking app flows on mobile simulators and emulators
• Investigating failed tests through reports and traces

用于编写和修改OpenClaw在Docker中的端到端测试，结合模拟服务器与真实服务，核查实际发送的请求、图像理解结果及用户最终看到的聊天回复。

• 添加或修改Docker端到端测试
• 核查发往依赖服务的请求内容
• 验证真实模型服务的行为

围绕用户操作与可见结果，为React组件和钩子编写或修复测试，模拟网络响应并检查无障碍问题，同时判断哪些内容需要在真实浏览器中验证。

• 为React表单和组件补充测试
• 验证自定义钩子与异步更新
• 模拟API成功与失败响应

Check a DeerFlow installation from code updates through deployment and basic service checks. Supports local and Docker setups, verifies frontend pages and API health, and produces a report with results and troubleshooting recommendations.

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• Checking DeerFlow after installation
• Verifying startup after a code update
• Checking a Docker deployment

Set up Pact tests that record what a frontend expects from an API and verify those expectations against the backend. Review these contract tests to catch incompatible changes and help services be tested and deployed independently.

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• Set up tests for frontend and backend API compatibility
• Check whether services can be deployed independently
• Replace selected slow end-to-end tests with contract tests

Add end-to-end tests, which check complete usage flows, and API tests for features that already work. Follow the project's existing test setup to extend automated coverage without introducing a separate testing approach.

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• Adding automated tests to an existing feature
• Testing complete usage flows with E2E tests
• Adding API tests using the existing test setup

Design machine learning workflows from data preparation through training, validation, deployment, and monitoring. Use templates and guidance to connect stages, track versions and experiments, handle failures, and plan gradual releases with rollback options.

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• Designing an end-to-end machine learning pipeline
• Building reproducible training workflows
• Comparing models before production deployment

Build end-to-end tests with Playwright and Cypress to check complete user workflows, such as login and checkout. Improve test reliability through stable element selection, independent test data, appropriate waits, and debugging with traces and screenshots.

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• Automate tests for login and checkout workflows
• Investigate tests that fail intermittently
• Run browser tests in CI/CD pipelines

Turn a project idea into a detailed system plan before coding. Organize architecture, data flows, dependencies, and file-level tasks in a linked Markdown workspace, with research references, consistency checks, and saved state for resuming later.

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• Plan a new system before writing code
• Break implementation into tasks with files and dependencies
• Check a design for gaps and contradictions

Connect NanoClaw agents to DeltaChat for email-based messaging with end-to-end encryption. Set up direct chats or small group conversations, exchange file attachments, and link each chat to the appropriate agent group.

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• Chatting with a personal assistant through DeltaChat
• Using an agent in a small DeltaChat group
• Exchanging files with an agent in chat

Guide substantial qwen-code feature development from investigation and design through implementation, testing, and review. Produce design documents and end-to-end test plans, compare behavior before and after changes, and address verified review findings.

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• Developing features that span multiple files
• Documenting a design before implementation
• Comparing behavior before and after a change

Test Qwen Code CLI behavior from model requests through tool execution. Reproduce bugs, check terminal interactions and MCP tool connections, and inspect API logs using real models or mock servers for controlled scenarios.

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• Reproduce reported CLI bugs and verify fixes
• Test MCP tool connections through the CLI
• Check terminal rendering and keyboard interactions

Run Openwork end-to-end tests, which verify complete user journeys, locally or on Daytona. Check the exact commit and runtime, investigate failures or skipped tests, and report results with commands, counts, and an explicit overall verdict.

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• Running a single end-to-end test
• Verifying the exact commit intended for a PR
• Investigating skipped tests and missing prerequisites

Investigate failing or flaky NemoClaw end-to-end tests, which check complete workflows. Trace each assertion through its inputs and implementation, including cleanup and dependent jobs, and produce an evidence ledger to guide authorized repairs and reruns.

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• Investigate a failing end-to-end test
• Audit assertions that execution has not reached
• Review cleanup and dependent job requirements

Turn a vague research direction into a focused proposal and a detailed experiment roadmap. This workflow connects method refinement with validation planning, producing review records, an experiment tracker, and a summary of what to run next.

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• Turn a rough research idea into a focused proposal
• Plan experiments that test the paper's claims
• Organize experiment order, budget, and decision points

Coordinate a research project from a broad topic through literature review, idea selection, experiments, and iterative review. Produce a research summary for writing, with optional paper drafting and PDF compilation, while recording stage progress for later resumption.

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• Taking a broad research topic through experiments and review
• Coordinating experiment implementation and result collection
• Preparing an evidence-based handoff for paper writing

Prepare a conference talk from a completed paper, including an outline, Beamer slides, editable PPTX, speaker notes, and a full script. Polish the visuals, check exported files, and optionally audit claims, citations, and anonymity.

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• Prepare a full conference talk from a completed paper
• Create Beamer slides and an editable PPTX
• Prepare speaker notes, a talk script, and Q&A

Verify app changes through real user journeys and produce a single HTML demonstration. Each step connects a claim, user action, observable check, narration, and validated screenshot so reviewers can inspect evidence that the experience works.

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• Show end-to-end evidence for a feature or bug fix
• Check that core behavior survives a refactor
• Prepare a narrated HTML demonstration for PR review

Launch the real iPolloWork app on Daytona or locally and run scripted end-to-end tests through its debugging connection. Collect machine-checkable assertions, validated screenshots, and reports as evidence of the tested behavior.

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• Run scripted end-to-end tests on Daytona
• Collect screenshots and reports for a pull request
• Run tests locally when Daytona is unavailable

Build CI workflows that use mirrord to test applications against services in a real Kubernetes cluster. Configure runner access, start and stop application sessions, validate configuration files, and troubleshoot connection, permission, and logging problems.

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• Run integration and end-to-end tests against staging
• Create mirrord workflows for GitHub Actions or GitLab CI
• Configure Kubernetes access from a CI runner

Review designs, products, and features with Steve Jobs' standards: ruthless simplicity, focus, and end-to-end excellence. Use when the user mentions "Steve Jobs review", "design review", "product review", "what would Steve do", "insanely great", "this feels too complicated", "too many features", "product taste", "saying no", or "is this good enough to ship". Also trigger when critiquing a UI, feature, or roadmap for focus and simplicity, cutting scope to the essential, or pressure-testing the whole experience from first run to daily use. Covers the simplicity audit, the no list, design-is-how-it-works, end-to-end ownership, demo culture, and a Jobs-style review protocol with binary verdicts. For visual design fundamentals, see refactoring-ui. For usability audits, see ux-heuristics. For detail polish, see microinteractions.

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