「rag」の検索結果

Harden iOS/Android apps you ship: storage, TLS pinning policy, IPC, and backend trust. You still enforce authz on the server.

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。

Refactor Spring Boot and Java code to improve maintainability, readability, and adherence to enterprise best practices. This skill transforms messy Spring Boot applications into clean, well-structured solutions following SOLID principles and Spring Boot 3.x conventions. It addresses fat controllers, improper transaction boundaries, field injection anti-patterns, and scattered configuration. Leverages Java 21+ features including record patterns, pattern matching for switch, virtual threads, and sequenced collections.

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Harden IAM, storage, keys, and org policies in cloud accounts you administer. Focus on identity, logging, and public-exposure controls.

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Provides integration patterns for LangChain4j with Spring Boot. Configures AI model beans, sets up chat memory with Spring context, integrates RAG pipelines with Spring Data, and handles auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications, building Java LLM applications with @Bean configuration, or setting up Spring AI patterns.

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Audits token storage mechanisms to prevent XSS-based JWT theft.

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Use when implementing caching, session storage, rate limiting, or any Redis integration. Covers cache-aside pattern, key naming, TTL strategy, and serialization config.

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Configura cobertura de tests y CI pipeline

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Azure Key Vault SDK for Python. Use for secrets, keys, and certificates management with secure storage.

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Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl.

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First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

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AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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Android data layer implementation guide. Provides comprehensive patterns for Room Database (Entity, DAO, Migration), DataStore (Preferences), Repository layer design, and common pitfalls. Use when implementing local data storage, cache strategies, or data source integration in Android projects.

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Earnings-season triage across ALL active theses (not just Live Portfolio holdings) — every earnings call reported inside the window gets a Quartr event summary, a Conviction-Trigger/Outstanding-Questions cross-reference, and a coverage check against existing Research notes, producing a ranked deep-read queue for /transcript. Use when user says "earnings sweep", "who reported", "triage earnings", "catch up on earnings season", or after any earnings-heavy stretch. Default window 14 days; `/earnings-sweep 90` covers a full season.

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Validate feature-level integration after all tasks are implemented. Checks cross-task consistency, full test suite, and overall spec coverage.

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Clean, high-contrast enterprise design for data-driven workflows with intuitive drag-and-drop patterns and structured layouts.

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Generate a single-file product landing page with a layered ASCII cosmos hero (rotating ASCII planet, drifting irregular asteroids, comet trails, nebula gas clouds — each in its own harmonious color) plus full marketing sections (about / features grid / showcase / spec / pricing / CTA / footer). Takes a natural-language description of one product (any kind — a note app, a coffee subscription, a CLI tool, an indie hardware, a hosting service…) and outputs ONE working .html file with deep-space dark or warm-letterpress theme. Runs in BOTH Claude Code (writes to ~/Desktop) and GLM / online chat (outputs HTML inline). Trigger phrases: "做个宇宙风产品落地页", "生成 ASCII 产品官网", "ascii-cosmos-gen ...", "做个独立软件 / 独立硬件落地页", or when user drags this skill folder into chat asking for an atmospheric product landing page.

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Generate a single-file Chinese atelier-style portfolio website (horizontal-row list + hover-reveal thumb interaction, art lishu typography "Alimama DaoLiTi" via CDN, light/dark theme, hash-routed detail pages). Takes a natural-language description of the studio (name, director, discipline, works) and outputs ONE working .html file. Runs in BOTH Claude Code (writes to ~/Desktop) and GLM / online chat (outputs HTML inline). Trigger phrases include "做个中式工作室作品集", "做个隶书作品集", "lishu-portfolio-gen ...", "做个白屋风格的作品集", or when user drags this skill folder into chat asking for an atelier-style site.

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Independent quality assurance for one SDD Composy task in qa_required: CA coverage, unit/integration/E2E, accessibility, responsiveness, environment, and evidence inventory, producing the QA report and requesting evidence_required. Use when a task finished execution — 'rodar o QA da task', 'testar a TASK-003', 'validar a implementação'. Do NOT use for code review (sdd-review), the final verdict (sdd-verify), or test runs outside an SDD task.

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Plan explicitly authorized read-only production observations and trace evidence-backed causes into preventive regression coverage without external effects.

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Select traceable regression coverage from change impact, affected risks, criteria, dependencies, and prior defects rather than execution convenience.

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Design traceable Web and browser checks with explicit browser coverage, observed interactions, isolated sessions, and evidence limitations.

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Execute an explicitly authorized exploratory charter and record notes, findings, evidence, and follow-up without claiming false coverage.

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Review requirements, coverage, results, evidence, and findings without changing the product or recorded state.

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。