「agent response」の検索結果

MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.

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Validates business ideas through customer conversations using Rob Fitzpatrick's Mom Test framework. Use when planning user interviews, getting product feedback, validating ideas, designing discovery questions, or extracting honest signal from biased customer responses. Covers good vs bad questions, deflecting compliments, anchoring fluff, pressing for commitment, and customer slicing.

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Write idiomatic Kotlin 1.9+ with null safety, sealed classes, data classes, extension functions, delegates, collections, inline/reified generics, and expression syntax. Use for Kotlin language constructs, Java-to-Kotlin migration, lazy delegates, data classes, backing properties, or inline/reified generics; keep language constructs in scope even inside response models, and defer coroutine configuration, Android Context/framework, Retrofit/OkHttp client setup, and other library-specific recipes.

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Implement Global Exception Filters and standard error formats in NestJS. Use when implementing global exception filters or standardizing error responses in NestJS.

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NIST SP 800-61r3-aligned incident triage that preserves evidence, separates analysis from authorization, and records status. Use for incident intake, severity assessment, containment readiness, or evidence preservation; not generic debugging or unscoped response.

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Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.

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Generate complete, runnable Volcengine SDK code and provide SDK configuration guidance. Supports Go, Python, PHP, Java, and Node.js. Trigger this skill whenever the user wants to call a Volcengine API, generate Volcengine SDK code, or describes a cloud operation on Volcengine (e.g., "list ECS instances", "create a VPC on Volcengine", "query Volcengine billing with Python"). Also trigger when the user asks about Volcengine SDK configuration and best practices — including retry, timeout, authentication (AK/SK, STS, AssumeRole), proxy, connection pooling, SSL, debug mode, and error handling (e.g., "how to configure retry for Volcengine Go SDK", "volcengine python sdk proxy setup"). Trigger when the user mentions Volcengine service names such as ECS, VPC, CDN, CLB, RDS, Redis, Kafka, billing, IAM, DNS with code generation or SDK usage intent. When the user only needs API specification queries (parameters, error codes, response structures), hand off to the volcengine-api skill. When the user needs CLI-based operations, hand off to the volcengine-cli skill. Supports both Chinese and English prompts.

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Query and answer questions about Volcengine API specifications. Trigger this skill whenever a user asks about Volcengine API parameters, error codes, request methods, enum values, required fields, response structures, pagination, parameter dependencies, or API comparisons — even if they don't explicitly say "API". Typical triggers include questions like "What parameters does DescribeInstances have?", "What values does Status support?", "What does InvalidInstanceId.NotFound mean?", "Does Volcengine have a batch tag deletion API?", "Which APIs does ECS support?", "How do I pass parameters to CreateDatabase?", "Is ChargeType required?", "What fields does DescribeInstances return?", "How do I paginate instance lists?", "What's the difference between these two APIs?", "RunInstances returns InvalidParameterValue". When the user needs runnable SDK code, hand off to the volcengine-sdk-generator skill. When the user needs CLI-based operations, hand off to the volcengine-cli skill. Supports both Chinese and English prompts.

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Operational skill hub for LLM system architecture, evaluation, deployment, and optimization (modern production standards). Links to specialized skills for prompts, RAG, agents, and safety. Integrates recent advances: PEFT/LoRA fine-tuning, hybrid RAG handoff (see dedicated skill), vLLM 24x throughput, multi-layered security (90%+ bypass for single-layer), automated drift detection (18-second response), and CI/CD-aligned evaluation.

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Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.

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Interactive scientific visualization with Plotly. Two APIs: plotly.express (px) for one-liner DataFrame plots, plotly.graph_objects (go) for trace-level control. 40+ chart types with hover, zoom, pan, animation. Exports HTML or static PNG/SVG/PDF via kaleido. Use for volcano plots with gene hover, dose-response dashboards, expression heatmaps, 3D molecular views. Use seaborn for stats; matplotlib for publication figures.

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Provides and generates LangChain4j tool and function calling patterns: annotates methods as tools with @Tool, configures tool executors, registers tools with AiServices, validates tool parameters, and handles tool execution errors. Use when building AI agents that call tools, define function specifications, manage tool responses, or integrate external APIs with LLM-driven applications.

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Email generation for construction workflows: RFI responses, submittal transmittals, meeting notices, change order notifications. Professional templates with context-aware content.

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Complete RFI (Request for Information) management system. Create, track, route, and analyze RFIs with automatic notifications and response deadline tracking.

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Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools required.

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Guides AI agents through the complete GDPR Data Subject Access Request (DSAR) workflow under Article 15, including identity verification, 30-day deadline calculation with extensions, response formatting, exemptions, and fee provisions. Activate when handling DSAR, access request, subject access, Art. 15, or SAR queries.

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California consumer privacy rights workflow implementation under CCPA/CPRA. Covers right to know, delete, opt-out of sale/sharing, correct, and limit sensitive PI processing. Includes 45-day response timelines, identity verification procedures, and authorized agent handling.

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Create tailored sales proposals and RFP responses that address prospect needs, articulate solution value, and include pricing, timelines, and social proof. Use when the user requests proposal generation or provides relevant inputs for this workflow.

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Classify, prioritize, and route incoming support tickets by extracting intent and entities, assigning severity, and generating initial responses. Use when the user requests ticket triage or provides relevant inputs for this workflow.

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Draft a professional, audience-aware email or reply with calibrated tone and a clear call to action. Use when the user needs one message, response, follow-up, support note, or meeting request; use sales-email-sequences for a coordinated multi-touch outbound campaign.

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Think and work like an expert Geomorphologist. Use when a task calls for Geomorphologist judgment. Reasons from coupled form, process, and time and from rates, thresholds, and lag times through field mapping, lidar/SfM DEM morphometry (chi profiles, Ksn in LSDTopoTools/Landlab), cosmogenic nuclide dating (CRONUS-Earth, OSL, U-Th), and landscape-evolution models, while treating equifinality, inheritance, DEM artifacts, and steady-state assumed over transient response as first-class failure modes.

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Think and work like an expert Immunotherapy Scientist. Use when a task calls for Immunotherapy Scientist judgment. Reasons from antigen recognition and checkpoint circuits through CAR-T/bispecific design, ASTCT CRS/ICANS grading, flow cytometry release CQAs, iRECIST response assessment, COMPASS/TIDE biomarker modeling, and JACIE/FACT IEC accreditation while treating antigen escape, pseudoprogression, tonic signaling, and step-up CRS as first-class failure modes.

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Think and work like an expert Crop Scientist. Use when a task calls for Crop Scientist judgment. Reasons from genotype-by-environment-by-management interaction, yield-component partitioning, and phenology-gated critical periods through MET stability analysis (AMMI, Finlay-Wilkinson, GGE biplots), mixed models (ASReml-R, lme4), N-response curves (quadratic-plateau, MRTN), and crop models (APSIM, DSSAT) while treating pseudo-replicated subsamples, single-site yield champions, uncorrected harvest moisture, and weather-during-anthesis confounding as first-class failure modes.

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Think and work like an expert Clinical Pharmacologist. Use when a task calls for Clinical Pharmacologist judgment. Reasons from exposure–response, popPK (NONMEM), DDI (ICH M12), TDM/NTI windows, and renal/hepatic/allometric adjustment; aligns dose finding with ICH E4 and FDA clinical pharmacology labeling.

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。