「app」の検索結果

Web and App implementation guide for Aurora UI. Trigger when user wants gradient glows, color blobs, and atmospheric lighting effects.

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One sentence - what this skill does and when to invoke it

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Build natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.

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Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.

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Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.

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Production-grade Android app development guide covering native (Kotlin/Java), cross-platform (Flutter, RN, KMM), and hybrid architectures.

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Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.

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A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.

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Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.

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When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for Ch...

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Web and App implementation guide for AI Native UI. Trigger when user wants conversational interfaces, adaptive layouts, and generative AI aesthetics.

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Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS...

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Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimi...

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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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Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.

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Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill ...

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You bring the third dimension to the web. You know when 3D enhances and when it's just showing off. You balance visual impact with performance. You make 3D accessible to users who've never touched a 3D app. You create moments of wonder without sacrificing usability.

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Web and App implementation guide for 3D UI. Trigger when user wants actual 3D objects, perspective effects, and spatial depth.

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Detect lateral movement in network traffic using Zeek (formerly Bro) log analysis. Parses conn.log, smb_mapping.log, smb_files.log, dce_rpc.log, kerberos.log, and ntlm.log to identify SMB file transfers, NTLM account spray activity, remote service execution, and anomalous internal connections.

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Detect model stealing, model inversion, and membership inference performed through inference-API abuse by monitoring query patterns, applying output perturbation, and red-teaming your own model's extractability.

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Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification.

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Detect process hollowing (T1055.012) by analyzing memory-mapped sections, hollowed process indicators, and parent-child process anomalies in EDR telemetry.

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Detect DLL side-loading attacks where adversaries place malicious DLLs alongside legitimate applications to hijack execution flow for defense evasion.

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Detects prompt injection attacks targeting LLM-based applications using a multi-layered defense combining regex pattern matching for known attack signatures, heuristic scoring for structural anomalies, and transformer-based classification with DeBERTa models. The detector analyzes user inputs before they reach the LLM, flagging direct injections (system prompt overrides, role-play escapes, instruction hijacking) and indirect injections (encoded payloads, multi-language obfuscation, delimiter-based escapes). Based on the OWASP LLM Top 10 (LLM01:2025 Prompt Injection) and Simon Willison's prompt injection taxonomy. Activates for requests involving prompt injection detection, LLM input sanitization, AI security scanning, or prompt attack classification.

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。