「end-to-end」の検索結果

Build or revise Godot UI from an approved design, separated art, or a visual reference when scene structure, gameplay binding, and runtime visual verification all matter. Use for complete Godot UI integration; use ordinary Godot UI guidance for isolated node or layout questions that do not require an end-to-end visual workflow.

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End-to-end app feature inventory and user-story testing workflow with a canonical tracker. Use when the user asks to audit every feature, derive expected behavior from code, test user journeys, or explicitly fix and retest documented UX or logistical defects.

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end open source contribution workflow: from scanning issues to submitting PRs. Use this skill whenever the user wants to contribute to an open source project, find issues to fix, submit a pull request, fork a repo to contribute, fix a GitHub issue, or mentions 'open source contribution'. Also trigger when they provide a GitHub repo URL and ask about contributing, say things like 'help me submit a PR', 'find good first issues', 'I want to contribute to X', or mention fixing bugs in someone else's project.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the reasoning style of Kaiming He, computer vision pioneer and creator of ResNet. Use this skill whenever you are designing deep learning architectures, debugging neural network optimization, formulating generative AI problems, or bridging AI with other scientific domains. Trigger this skill for discussions on network depth, weight initialization, residual learning, flow matching, or when reframing discriminative tasks as conditional generation. It emphasizes simplicity in complex visual problems, end-to-end optimization, and viewing AI as a universal language for science.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the mental models and frameworks of Andrej Karpathy (deep learning, former Director of AI at Tesla, founding member of OpenAI, Eureka Labs). Use this skill whenever you are helping the user build neural networks from scratch, debug deep learning pipelines, evaluate AI agent workflows, design LLM apps, or navigate the transition to Software 3.0 (vibe coding). It is highly relevant for pedagogy (untangling complex knowledge), assessing AI capabilities vs. limitations (jagged intelligence, tokenization limits), and architectural decisions (end-to-end optimization vs. complex pipelines). Reach for this whenever discussing LLM training, autonomous systems, or AI-assisted coding.

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Applies the reasoning, principles, and mental models of Sebastian Thrun (robotics and self-driving cars pioneer, founder of Google X, Waymo, Udacity, Stanford University). Reach for this skill whenever Claude is asked to advise on hardware/software systems engineering, autonomous vehicles, moonshot ideation, probabilistic robotics (SLAM), or leading high-stakes engineering teams. Trigger this skill for discussions on democratizing education, regulating AI, transitioning from academic research to product development, or managing technical teams with empathy. Use it to shift focus from incremental component debates to end-to-end execution and audacious goals.

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Run the end-to-end viewer smoke test (`tests/viewer_smoke.sh`). Spawns `rezolus view` in upload-only, file, A/B, and proxy modes, exercises the API endpoints, and verifies experiment attach/detach. Use after any change touching `src/viewer/` or before opening a viewer-related PR.

日本語の概要は準備中です。原文の説明を表示しています。

Full-stack autonomous math modeling agent for CUMCM (全国大学生数学建模竞赛). Reads the problem statement and data, iterates through research → coding → verification → LaTeX writing, and produces a publication-quality PDF paper. Use when the user provides a CUMCM problem and wants end-to-end automated modeling, coding, and paper generation.

日本語の概要は準備中です。原文の説明を表示しています。

Full-stack autonomous math modeling agent for MCM/ICM (美国大学生数学建模竞赛). Handles team control number, problem choice (A–F), English academic writing, mcmthesis LaTeX template, and optional practical deliverable (memo/letter/report). Use when the user provides an MCM/ICM problem and wants end-to-end automated modeling, coding, and paper generation in English.

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Generates comprehensive test scenarios from requirements including BDD/Gherkin scenarios, unit tests, integration tests, and end-to-end test cases. Use when converting requirements, user stories, or specifications into testable scenarios with full coverage including happy paths, error cases, edge cases, and boundary conditions. Outputs structured test suites ready for implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Scaffold end-to-end testing infrastructure. Use when the user says "e2e scaffold" or "set up e2e testing"

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end workflow for building a new Terrae component from scratch

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Use when the user asks to take a feature or bug fix from prompt to implementation, especially prompts like "/create a new feature", "build this feature end-to-end", "take this from plan to PR", or "own this change through validation and handoff". This skill is for repo-local delivery workflows that must create and maintain implementation plans, choose appropriate tests, run deterministic validation, open a draft PR against main, and return the preview deployment URL when one is available.

日本語の概要は準備中です。原文の説明を表示しています。

Do a task end-to-end — implement, PR, CI loop, ship

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment + paper). Meta-skill that chains the four downstream skills in order. Pure markdown, no Python runtime.

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end 3D printing for Bambu Lab printers. Finds models online (MakerWorld, Printables), generates them with AI (text-to-3D, image-to-3D) or as exact-dimension parametric CAD, checks and repairs printability, converts textures to AMS multi-color, renders previews, opens them in Bambu Studio for the user to print, and reads printer status, AMS filaments and print progress. Use this whenever the user wants to 3D print something, design or model an object for printing, work with STL/3MF/OBJ/GLB files for a printer, check on a Bambu Lab printer (A1, A1 Mini, A2L, P1S, P2S, X1C, X1E, X2D, H2C, H2S, H2D, H2D Pro), or asks about AMS filament, slicing or print progress, even if they don't say "Bambu".

日本語の概要は準備中です。原文の説明を表示しています。

Inspect an unfamiliar repository, interpret a broad Markdown user journey at runtime, operate the real product through its supported web, API, CLI, desktop, or mobile surface, and produce an auditable pass, fail, or blocked judgment with screenshots, logs, recordings, and a step timeline when available. Use when asked to run smoke tests, validate an end-to-end user journey, dogfood a product, test a release candidate, or execute a non-deterministic workflow that may include authentication or human checkpoints. Do not use as a substitute for deterministic unit, integration, or scenario tests.

日本語の概要は準備中です。原文の説明を表示しています。

Manages software projects end-to-end — decomposing work into tasks, tracking progress across sprints, generating status reports, and integrating with tools like Jira, Linear, GitHub Issues, and Trello. Use when the user requests project management or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting. Use when the user requests testing or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Train machine learning models end-to-end, covering data loading, preprocessing, architecture selection, training loops, validation, and checkpointing. Use when the user requests model training or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Prepare personalized email outreach by researching prospects, verifying email addresses, building company context, and generating relevant talking points. End-to-end outreach preparation from prospect identification to send-ready intelligence.

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal, denoising with OBITools3 or DADA2, contamination filtering, taxonomy assignment, Hill number diversity, and constrained ordination. Use when processing environmental DNA samples for biodiversity assessment or ecological surveys.

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End-to-end DNA sequencing workflow from FASTQ files to variant calls. Covers QC, alignment with BWA, BAM processing, and variant calling with bcftools or GATK HaplotypeCaller. Use when calling variants from raw sequencing reads.

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End-to-end CRISPR experiment design from target selection to delivery-ready constructs. Covers guide RNA design, off-target assessment, and specialized editing strategies including knockouts, base editing, and HDR knockins. Use when designing complete CRISPR editing experiments for gene knockout, correction, or tagging.

日本語の概要は準備中です。原文の説明を表示しています。