「language」の検索結果

Restate the last message in plain human language, with no jargon.

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。

Reusable skill for coding agents to build mediahost integrations, API clients, scrapers, bulk downloaders, and media tools. Incorporates the unofficial Python wrapper, auth flow, endpoints, rate-limit handling, and cross-language patterns ...

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。

Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

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。

Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

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。

Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications. Triggers: "text translation", "translator", "translate text", "transliterate", "TextTranslationClient".

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。

Build translation applications using Azure Translation SDKs for JavaScript (@azure-rest/ai-translation-text, @azure-rest/ai-translation-document). Use when implementing text translation, transliteration, language detection, or batch document translation.

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。

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.

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。

Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.

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。

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings.

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。

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。

Correlates security events in IBM QRadar SIEM using AQL (Ariel Query Language), custom rules, building blocks, and offense management to detect multi-stage attacks across network, endpoint, and application log sources. Use when SOC analysts need to investigate QRadar offenses, build correlation rules, or tune detection logic for reducing false positives.

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。

Configure AWS Verified Access to provide VPN-less zero trust network access to internal applications using identity and device posture verification with Cedar policy language.

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。

Build effective detection rules using Splunk Search Processing Language (SPL) correlation searches to identify security threats in SOC environments.

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。

Leverages Splunk Enterprise Security and SPL (Search Processing Language) to investigate security incidents through log correlation, timeline reconstruction, and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and authentication data analysis. Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident investigation.

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。

Create or update the feature specification from a natural language feature description.

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。

Create or update feature specifications from natural language descriptions. Use when starting new features or refining requirements. Generates spec.md with user stories, functional requirements, and acceptance criteria following spec-driven development methodology.

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。

Secure Solana wallet generation using official Solana Labs libraries — Ed25519 keypairs, memory zeroization, vanity address generation, offline-only operation, and multi-language implementations (Rust, TypeScript, Bash).

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。

Multi-language test infrastructure for the Pump SDK — Rust unit/integration/security/performance tests, TypeScript Jest tests, Python fuzz tests, shell test orchestration, Criterion benchmarks, and CI quality gates.

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。

Edit PDFs with natural-language instructions using the nano-pdf CLI.

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。

CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).

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。

Explicit-only request to restate the previous explanation plainly in the current conversation language while preserving facts and uncertainty.

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。

Build and sharpen a project's domain model. Use only when actively changing glossary or ubiquitous-language terms, or recording a durable architectural decision; merely reading a glossary is not a trigger.

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。

Generic helpdesk first-response skill for creating KB-based response drafts. Use when handling support tickets, creating response templates, or building a structured helpdesk workflow. Supports error code detection, keyword matching, confidence scoring, multi-language templates, and escalation workflows. Customize by providing your own KB articles and configuration.

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。

Android device offensive security, forensic extraction, and mobile app exploitation. Use this whenever the user needs to: break into or bypass the lock screen of an Android phone, extract data from a seized Android device for evidence, analyze or reverse-engineer an APK to find vulnerabilities, intercept communications on an Android device, exploit Android apps via deeplinks, steal crypto wallets or app data, set up rogue WiFi to target a phone, or plan any mobile device investigation or penetration test. Also trigger when the user mentions Android forensics, mobile pentesting, law enforcement phone extraction, device exploitation, WhatsApp or Telegram extraction from a phone, Android app reversing, CVE research for Android, or needing a chain of custody for mobile evidence. Even if the user describes the scenario casually or in another language, if they need to gain access to or pull data from an Android phone, use this skill.

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。