「validation」の検索結果

Apply pytorch geometric in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses pytorch geometric or its strengths fit the task.

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。

Apply sql optimization patterns in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses sql optimization patterns or its strengths fit the task.

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。

Apply sql queries in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses sql queries or its strengths fit the task.

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。

Apply shap in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses shap or its strengths fit the task.

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。

Apply stable-baselines3 in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses stable-baselines3 or its strengths fit the task.

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。

Apply hugging face datasets in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses hugging face datasets or its strengths fit the task.

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。

Apply matplotlib in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses matplotlib or its strengths fit the task.

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。

Apply experimental design in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses experimental design or its strengths fit the task.

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。

Apply dbt transformation patterns in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses dbt transformation patterns or its strengths fit the task.

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。

Apply data visualization in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses data visualization or its strengths fit the task.

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。

Apply airflow dag patterns in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses airflow dag patterns or its strengths fit the task.

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。

Apply data context extractor in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses data context extractor or its strengths fit the task.

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。

Apply backtesting frameworks in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses backtesting frameworks or its strengths fit the task.

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。

Apply dask in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses dask or its strengths fit the task.

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 preparing a Formax code handoff: selecting files, generating repomix bundles, and writing a high-quality prompt for WebGPT or another coding agent with clear constraints and validation scope.

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。

Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.

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。

Design analytics-driven browser test matrices and execute cross-browser tests. Covers BrowserStack/Sauce Labs configuration, Playwright browser channels, common cross-browser CSS/JS divergences, a known-issues documentation log, and progressive enhancement validation. Use when: "cross-browser," "browser matrix," "BrowserStack," "Safari issues," "browser compatibility," "Edge," "works in Chrome but not Safari." Not for: pixel-level baseline strategy and threshold tuning — use visual-testing; device-farm testing of native/hybrid apps — use mobile-testing. Related: visual-testing, playwright-automation, ci-cd-integration, mobile-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。

Validate release readiness with evidence-based go/no-go decisions. Covers go/no-go checklists, smoke test suite design, staged rollout validation, rollback criteria and procedures, and post-deployment verification. Ensures release confidence comes from data, not feelings. Use when: "release ready," "go/no-go," "smoke test," "release checklist," "rollback plan," "staged rollout," "canary deploy." Not for: safe-release techniques (flags, canary, dark launch) applied during the rollout itself — use testing-in-production; scheduled probes that run continuously after release — use synthetic-monitoring; designing new tests from prod telemetry — use observability-driven-testing. Related: testing-in-production, qa-metrics, ci-cd-integration, ai-system-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。

Validate database integrity, test migrations forward and backward, verify schema constraints, manage seed data, detect migration drift, and identify query performance issues. Covers PostgreSQL, MySQL, MongoDB with Prisma, TypeORM, Drizzle, and SQLAlchemy, plus Testcontainers test databases. Use when: "database test," "migration test," "migration rollback," "rollback test," "data integrity," "SQL test," "schema validation," "seed data," "query performance," "Testcontainers." Not for: synthetic data generation/masking at scale — use test-data-management; Docker/IaC test-environment provisioning — use test-environments; SQL injection — use security-testing. Related: test-data-management, test-environments, security-testing, ci-cd-integration.

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 for WCAG 2.2 AA compliance with axe-core + Playwright, keyboard navigation audits, screen reader testing, ARIA pattern validation, and legal compliance mapping (ADA, EAA, Section 508). Automated tools catch 30-40% of issues — this skill covers automated and manual testing together. Use when: "accessibility," "a11y," "WCAG," "screen reader," "axe," "keyboard navigation," "ARIA," "ADA compliance." Not for: cookie-consent/GDPR compliance — use compliance-testing; pixel-diff visual regression — use visual-testing. Related: playwright-automation, compliance-testing, visual-testing, ci-cd-integration.

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 AI/LLM features that ship in your product. Covers prompt regression testing, response quality evaluation, tool-call validation, hallucination and RAG grounding checks, nondeterministic-output strategies, red-team/safety scans, eval frameworks, and agent-as-target injection (indirect injection via tool output / RAG / scan reports, self-propagating payloads, data exfiltration via an agent) plus a bundled detector for untrusted content. Use when: "test our LLM feature," "prompt regression test," "eval framework," "hallucination test," "RAG grounding," "nondeterministic output," "AI feature testing," "red-team our chatbot," "indirect prompt injection," "agent reading untrusted tool output," "production AI quality." Not for: using AI to generate your own test code — use ai-test-generation. Not for: classifying CI failures with AI — use ai-bug-triage. Not for: EU AI Act / GDPR conformity of an AI feature — use compliance-testing. Not for: canary/flag rollout of an AI feature — use testing-in-production. Related: ai-test-generation, ai-qa-review, api-testing, compliance-testing, security-testing, risk-based-testing, test-data-management.

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。

Establish the shared environment, source/runtime correspondence, target confirmation and validation evidence for MetaX vLLM upgrades. Use as the common prerequisite of the patch, attention, registry and model upgrade skills, or for an explicitly requested MetaX environment preflight; it does not perform domain-specific adaptations.

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 a structured implementation plan from an evidence draft. Validate paths, obtain configured independent Codex and Qoder reviews, synthesize available advice against repository evidence, preserve the draft, and produce testable acceptance criteria and validation steps.

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。

Symfony UX LiveComponent for reactive server-rendered UI -- components that re-render via AJAX on user interaction, zero JavaScript required. Use when building live search, real-time filtering, dynamic forms, inline validation, dependent selects, auto-save, polling, deferred/lazy rendering, or any UI that updates itself based on user input. Code triggers: AsLiveComponent, LiveProp, LiveAction, data-model, data-loading, data-live-action-url, ComponentWithFormTrait, LiveListener, emit, defer, lazy, polling. Also trigger when the user asks "how to build a search that filters as I type", "how to validate a form in real-time", "how to make a reactive component in PHP", "how to build dependent selects", "how to defer component rendering", "how to communicate between components via emit", "how to bind a form to a LiveComponent". Do NOT trigger for static reusable UI without reactivity (use twig-component), pure client-side JS behavior (use stimulus), or page-level navigation (use turbo).

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。