「ai safety」の検索結果

Use when a task should repeat on a schedule or until a condition holds (CI until green, follow a PR to merge, review rounds until no blockers, daily session summary). Ships ready prompt templates with run and duration limits, stop conditions and go-gate safety rules, and per-harness loop invocation.

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。

Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute. Use when user wants to prevent destructive git operations, add git safety hooks, or block git push/reset in Claude Code.

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。

Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.

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。

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.

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。

Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library

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。

Evaluates and implements age estimation and verification technologies for online services. Covers facial age estimation, digital ID verification, self-declaration with risk assessment, AI-based age estimation, and the accuracy versus privacy tradeoff. Includes ICO guidance and euCONSENT framework. Keywords: age verification, age estimation, facial analysis, digital ID, children, online safety.

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。

Affiliate and sponsored content generator — create natural product review, comparison, and recommendation articles that comply with ステマ規制. Integrates compliance-checker for automatic legal safety. Supports review, comparison, and experience-based formats.

Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.

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。

Comprehensive PR code review for OneKey monorepo. Use when reviewing PRs, code changes, or diffs — covers security (secrets/PII leakage, supply-chain, AuthN/AuthZ), code quality (hooks, race conditions, null safety, concurrent requests), and OneKey-specific patterns (Fabric crashes, MIUI, BigNumber). Triggers on "review PR", "review this PR", "code review", "check this diff", "审查 PR", "代码审查", "review

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。

Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.

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。

Safety guardrails for destructive commands. Warns before rm -rf, DROP TABLE, force-push, git reset --hard, kubectl delete, and similar destructive operations. User can override each warning. Use when touching prod, debugging live systems, or working in a shared environment. Use when asked to "be careful", "safety mode", "prod mode", or "careful mode". (gstack)

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。

Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when asked to "review this PR", "code review", "pre-landing review", or "check my diff". Proactively suggest when the user is about to merge or land code changes. (gstack)

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。

Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.

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 a carrier asks which KPIs to track, how to build a fleet dashboard, what targets to set, cadence for reviewing metrics (daily / weekly / monthly / quarterly), and how to operationalize data into actions. Covers safety, operations, financial, driver, and customer KPIs.

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 this skill when the user asks about getting/maintaining motor carrier operating authority — USDOT number, MC number, BOC-3 process agent, insurance filing (MCS-90, BMC-91/91X), Unified Carrier Registration (UCR), International Registration Plan (IRP), International Fuel Tax Agreement (IFTA), state-level permits (NY HUT, KY weight distance, OR weight-mile, NM weight distance), new entrant safety audit, intra vs interstate, for-hire vs private. Cite 49 CFR 365, 387, 390.

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 this skill when the user asks specifically about preparing for the New Entrant Safety Audit (NESA) under 49 CFR 385 Subpart D — different from a Compliance Review. Covers what auditors look at, the 18-month window, automatic failure conditions, the 60-day fix window, what to NOT do, and how to convert from "new entrant" to permanent authority. Cite 49 CFR 385.301-321.

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 a manager, dispatcher, or safety director needs to have a coaching conversation with a driver — about a safety event (harsh brake, hard turn, distraction), an HOS violation, a customer complaint, a missed delivery, repeated minor incidents, or to deliver positive recognition. Covers conversation structure, language, documentation, and escalation.

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。

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders.

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。

Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.

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。

Analyze text and images for harmful content with customizable blocklists.

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。

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

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。

Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.

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。

Set up Claude Code git safety guardrails that block dangerous git commands before execution. Use when the user asks to prevent git push, hard reset, git clean, destructive checkout/restore, or branch deletion from Claude Code hooks.

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。

How to write modern Swift well — modeling with value types, Swift 6 data-race safety and approachable concurrency (@concurrent, main-actor-by-default, actors, task groups), protocols and generics (some vs any), API design, performance and ARC, Swift Testing, macros, and the modern language features agents don't know about yet. Use when writing, reviewing, or migrating Swift, or when a concurrency error, a hang, a data race, a retain cycle, or a performance problem needs fixing.

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。