「end-to-end」の検索結果

Add durable end-to-end tests for user/API-visible behavior. Detect or scaffold the E2E framework, write tests, run the app, and store evidence. Use for E2E, Playwright/Cypress, regression tests, or quality gates. Not exploratory QA.

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。

Run Ship's full production workflow from raw requirement to PR: design, dev, E2E, review, QA, refactor, and handoff. Use only for explicit /ship:auto, auto pipeline requests, or end-to-end delivery.

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。

Orchestrate the combat team: coordinates game-designer, gameplay-programmer, ai-programmer, technical-artist, sound-designer, and qa-tester to design, implement, and validate a combat feature end-to-end.

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 automated API and end-to-end tests for implemented features. Use when the user says "create qa automated tests for [feature]"

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 production workflow guidance for Blender — the order to assemble scenes (block-out → camera → light → forms → materials → detail → render → composite → export), critique protocols, time budgets, and recovery patterns. Use whenever the user asks to "make a complete scene / hero shot / production-quality render", "what's the right order to do this", "set up a full pipeline", or has a multi-step request crossing modeling + lighting + materials + rendering. Make sure to use this skill for any request that spans multiple phases of 3D work, even if the user does not say "workflow" — also covers "make a final image of X", "produce a hero render", "professional-looking result".

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。

Execute a plan or concrete work prompt end-to-end. Use when implementing from docs/plans, a spec path, or a clear build request; use ce-debug for open-ended bugs.

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。

[BETA] Hands-off end-to-end branch dogfood pass with browser testing, auto-fixes, regression tests, and fix commits.

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。

Run this Django app locally against a throwaway database and drive its pages over HTTP to observe a change working. Use when verifying student/cadmin page behavior end-to-end.

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。

Run, diagnose, or manually test the private Stacktape Console locally, especially when local API/UI behavior must use the shared dev RDS data, Cognito users, AWS services, OAuth callbacks, or provider webhooks. Use for Console dev-mode setup, deciding between UI-only and full mode, shared-dev migrations, and GitHub/GitLab/Bitbucket end-to-end 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。

Run this repo's CI end-to-end — the kolu-specific procedure on top of the odu runner: the odu MCP front door, banned opt-out flags, linux-only platform pinning, venue-pool leasing, fail-fast surfacing, e2e timing evidence, and the green-gate. Triggers on "run CI", "drive CI", "re-run the pipeline", "close the red check", "warm the pool". Runner mechanics live in the `/odu` skill.

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。

Test kolu's remote-host features (multi-host / padi-remote) in a real browser against a real remote box — the ONLY full end-to-end harness for this surface (real ssh provision, no mock). Covers the isolated nix-run invocation (or just dev, which bakes the same agent source), ssh- provisioning a real remote box without touching production or another user's box, the chrome-devtools drive sequence for host-switch / split / code-browser / per-host-canvas, PID-exact teardown, and the reproduce- first rule for any bug the feature surfaces. Triggers on "test remote hosts", "test multi-host", "test padi-remote", "verify the host switch", "browser-test a remote host change", or before claiming a remote-host fix works.

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。

Act as an end-to-end data scientist: turn business questions into defensible analysis, validated models, and decision-ready reports. Use whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, classification, regression); asks to review an existing analysis, notebook, or model for flaws; or needs results written up for decision-makers. Triggers in any language ("phân tích dữ liệu", "xây model dự đoán", "kiểm định A/B"), even when they never say "data science" or "statistics".

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。

Run the post-deploy send test that validates a freshly deployed or updated warp route end-to-end — real token transfers across the route's legs, delivery confirmation, and fee-accrual checks. Use when asked to send-test, round-trip, or validate transfers on a warp route. Defaults to a full collateral-mesh test for multi-collateral routes.

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 e-commerce product catalog generation — turn a folder of raw product photos into clean packshots, product cutouts, Amazon-style dimensions images, lifestyle scenes, and marketplace-ready listing variants for Amazon, Shopify, and Etsy. Powered by Bria.ai's product pipeline. Use when building a product catalog, batch-processing product photos, or creating packshots, cutouts, dimension images, lifestyle shots, or marketplace-compliant listing images at scale.

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。

Test and validate MaaFramework Pipeline JSON, recognition nodes, action nodes, CustomAction/CustomRecognition wiring, resource loading, and end-to-end task behavior. Use when running `run_pipeline`, checking OCR/TemplateMatch/ColorMatch ROI, validating `context.run_task()` results, auditing `action: Custom` or `recognition: Custom` registrations, or choosing the right resource-check command.

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。

Executes a four-phase feature addition workflow (Discovery, Planning, TDD Implementation, Verification) for Python projects. Use when adding a new feature end-to-end — discovering project structure and integration points, drafting a feature spec with MoSCoW-prioritized requirements and BDD acceptance criteria, implementing via test-first TDD cycles, then verifying with ruff lint, ty type checks, and behavior-focused regression and contract coverage.

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。

Verify that changed components are actually connected into the intended end-to-end system flow. Use when checking imports/exports, registrations, data/control flow, configuration consumption, call paths, and boundary compatibility after 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。

Produces a structured, end-to-end linear walkthrough of an unfamiliar codebase by orchestrating parallel subagents across four phases — discovery, tracing, validation, and synthesis. Use when onboarding to a new repository, understanding execution paths from entry points, generating navigable codebase documentation, or needing fact-checked coverage of architecture, deployment, testing, and operations.

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 research workflow skill for investment analysts and policy researchers. Three scope modes the user picks at trigger time — light (4-5 page decision memo, ~15 min, 0 charts), medium (12-15 page topic brief, ~1 h, 6-10 charts), heavy (flagship report 30-40 pages / 15k+ words, ~2-3 h, 25-35+ charts, multi-stage workflow, multi-LLM, PDF + Word + WeChat + HTML derivations). Reports default to English; the AI replies in the user's chat language. Battle-tested on real macro/policy/equity reports (e.g. Saudi Vision 2030 deep-dive). Triggers when user types /analyst-research, /flagship-research, or describes needs like "research report", "topic analysis", "investment research", "做研报", "投研报告", "主题分析", "深度分析", "policy assessment", "industry deep-dive". Not for: pure news commentary (use topic-brief), slide decks (use deckster-slide-generator), one-shot Q&A.

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。

Complete workflow for building, implementing, and testing goal-driven agents. Orchestrates building-agents-* and testing-agent skills. Use when starting a new agent project, unsure which skill to use, or need end-to-end guidance.

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 resume parsing (detect format → extract fields). Uses a combination of format detection, text extraction, and LLM parsing to normalize resume data.

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。

Run a high-thoroughness end-to-end implementation loop using clean worker worktrees, per-slice planning, implementation, explicit review/fix iteration, orchestrator integration, and final commit/PR drafting. Use when the user explicitly wants a Ralph/Wiggum-style loop, autonomous multi-agent execution, a delegated feature/bugfix carried from confirmed scope through review-ready completion, or RFC-driven implementation that should be reviewed, bumped to In Progress, decomposed into phases, and executed through nested sub-loops. Supports Codex subagents by default and external CLI workers such as OpenCode when explicitly requested and 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。

Audit and rewrite a YouTube channel end-to-end for 2026: name and @handle, banner (2560x1440 with the 1235x338 mobile/TV safe area), profile picture, About plus searchable keywords, trailer for non-subscribers vs featured video for subscribers, sections and playlist layout, watermark, links. Triggers on "optimize my YouTube channel", "rewrite my channel about", "fix my banner", "channel audit", "set my trailer". Converts a viewer into a subscriber. Not for writing a video title (use yt-title-optimizer).

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 to smoke-test the evolve pipeline, test tools, or verify the plugin works end-to-end. Also use when the user says 'dry run', 'smoke test', or 'test pipeline'.

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。