「safety」の検索結果

Claude adapter for PlainTab storage, IndexedDB, localStorage, schema version, migration, cleanup, import/export, and old-user upgrade safety work.

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Shift-left safety net for dbt/SQL model edits. Runs change impact assessment before edits, generates SQL validation queries after, and executes them via `/mc-validate run`. Delegates health and monitor creation to peer skills.

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 a warehouse for stale, unused, or redundant tables via the analyze_storage_costs MCP tool. Classifies waste patterns and table categories, computes safety tiers, and handles category drill-downs and lineage follow-ups.

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。

Adding JSDoc/TSDoc, updating READMEs, replacing any types with proper definitions, and adding high-value comments to complex logic. Use for documentation gaps or type 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。

Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.

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。

Remediating known failure patterns automatically from Triage diagnoses and Beacon alerts: runbooks with safety-tier classification, staged verification, rollback. Use for automated remediation.

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。

Implementing robust business logic, API integrations, data models, and reproducible AI image-generation code with type safety. Use for production implementation, Gemini image API pipelines, or interactive pair programming.

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。

LLMOps Architect: Run LLM features in production: model routing, evals, observability, caching, cost, safety.

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Full safety mode: destructive command warnings + directory-scoped edits. (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。

Safety guardrails for destructive commands. (gstack)

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Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, analyze media intelligence, and tell people from AI agents on a website (Agent Detection) using direct Resemble AI API calls

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Twitter/X Agent Operations SOP v2 — Rebuilt from real dual-account operations. Real data: • CN account: grew from 1,150 → 3,679 followers (~14 months), 1 tweet/day, OAuth1 direct post • EN account: Buffer API • Real incidents: cron silent-failed for 2 weeks unnoticed, analytics data off by 17×, thread performance worse than single posts What's new in v2: • Step-by-step onboarding (Q1→Q6), multiple choice wherever possible — no big forms • Mandatory daily log after every tweet + weekly report every Monday • Pre-publish safety checklist (agent must pass before posting) • Content pool tracker (used/unused) + alert when ≤3 items remain • Dual-account credential separation (CN: OAuth1 / EN: Buffer API) • MASTER-STATUS.md as the single source of truth — read + write every session 🇨🇳 Twitter/X Agent 运营 SOP v2 — 基于真实双账号运营经验重写。 开局对话式收集 context、强制日报+周报、发推前红线自检、素材库追踪、双账号凭证分离、MASTER-STATUS.md 单一真相来源。 真实数据：中文账号从 1,150 粉增长至 3,679 粉（约14个月），1条/天。 Triggers: "twitter运营" | "推特agent" | "发推SOP" | "AI代运营" | "推文日报" | "素材库" | "Buffer API" | "OAuth1发推" | "twitter automation" | "tweet sop" | "推特涨粉"

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Testing Craft CMS 5 plugins and modules with Pest — test isolation, database safety, and the markhuot/craft-pest-core harness. ALWAYS load when writing, running, fixing, or reviewing tests for a Craft plugin or module, and whenever a suite touches a real Craft install. Covers why rollback is opt-in, tests/Pest.php + tests/bootstrap.php wiring, phpunit.xml.dist <env> pins (force DB name + table prefix, default connection coordinates, pin CRAFT_ENVIRONMENT against server-scoped locks), why --configuration= defeats DB isolation, throwing fail-closed DB guards, installing the plugin under test, process-timezone pinning, per-test site fixtures, idempotent Install migrations, stale service caches when components get swapped, muting audit sinks, queue stubs, factories, HTTP/DB assertions, CI jobs.

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Reviews Rust FFI code for type safety, memory layout compatibility, string handling, callback patterns, and unsafe boundary correctness. Use when reviewing extern blocks, #[repr(C)] types, bindgen output, or code calling C/C++ libraries.

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Remix v2 performance, streaming, caching, and server/client boundaries. Use when configuring HTTP caching, server-only modules, hydration safety, or prefetch. Triggers on headers export, Cache-Control, PrefetchPageLinks, Link prefetch, .server.ts, .client.ts, useHydrated, ClientOnly, window.ENV, links preload, useId.

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Reviews Python code for type safety, async patterns, error handling, and common mistakes. Use when reviewing .py files, checking type hints, async/await usage, or exception handling.

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Reviews Go code for idiomatic patterns, error handling, concurrency safety, and common mistakes. Use when reviewing .go files, checking error handling, goroutine usage, or interface design. Covers generics (Go 1.18+), errors.Join and slog (Go 1.21+), and Go 1.22 loop variable semantics.

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。

Reviews Swift code for concurrency safety, error handling, memory management, and common mistakes. Use when reviewing .swift files for async/await patterns, actor isolation, Sendable conformance, or general Swift best practices.

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Reviews PostgreSQL code for indexing strategies, JSONB operations, connection pooling, and transaction safety. Use when reviewing SQL queries, database schemas, JSONB usage, or connection management.

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Conservative review of end-user legal exposure from diagnostics targets and probe hosts, by jurisdiction. Use when shipping or editing diagnostics target lists, probe hosts, or bootstrap endpoints.

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Use when reviewing Spring Boot 4 / Java 17+ code with concrete files or diffs — pull requests, modules, or pasted Java/Spring sources — for migration risks, architecture boundary leaks, JSpecify null-safety gaps, security flaws, performance regressions, or Spring Data pitfalls. Not for Kotlin-only code, non-Spring frameworks, or generic review advice without code context.

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Activates Warren Buffett's complete investment thinking system. The following scenarios must trigger it: analyzing any stock or company, evaluating investment opportunities, interpreting financial reports/annual reports/shareholder letters, assessing business moats or competitive advantages, evaluating management quality and integrity, making buy/hold/sell decisions, understanding core value investing concepts (compounding/intrinsic value/margin of safety/circle of competence/Mr. Market), analyzing any industry (insurance/banking/consumer/media/energy/railroads/technology), handling capital allocation/buybacks/dividends questions, assessing market sentiment and macro risks, exploring when to sell, analyzing institutional imperative or management behavior. Even if the user does not mention "Buffett," proactively trigger whenever the topic involves investment analysis, business quality assessment, or investment decision-making.

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Design guardrail layers — input classifiers, output validators, PII scrubbers, policy rule engines. Use when asked to "add safety filters", "scrub PII from LLM output", or "design content moderation".

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Expert-level skill for Rust programming (Rust 2024 / v1.85+). Covers memory safety, async, Axum/SQLx, CLI, and optimization in English and Indonesian.

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。