Results for “context”

Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.

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Create distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.

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Guide for when to use and when not to use return validators in Convex functions. Use this skill whenever the user is writing Convex queries, mutations, or actions and needs guidance on return value validation. Also trigger when the user asks about Convex type safety, runtime validation, AI-generated Convex code, Convex AI rules, Convex security best practices, or when they're debugging return type issues in Convex functions. Trigger this skill when users mention "validators", "returns", "return type", or "exact types" in the context of Convex development. Also trigger when writing or reviewing Convex AI rules or prompts that instruct LLMs how to write Convex code.

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One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.

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Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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Agent Ready project design context for navigation, docs links, and interface tone. Use when building or reviewing UI in this repo so patterns match the documented product feel.

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Generates Strategy pattern for PHP 8.5. Creates interchangeable algorithm families with context class, strategy interface, and concrete implementations. Includes unit tests.

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Generates PSR-3 Logger implementation for PHP 8.5. Creates LoggerInterface implementations with log levels, context interpolation, and LoggerAwareTrait usage. Includes unit tests.

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Generates State pattern for PHP 8.5. Creates state machines with context, state interface, and concrete states for behavior changes. Includes unit tests.

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Generates DDD Anti-Corruption Layer for PHP 8.5. Creates translation layer between bounded contexts or external systems. Includes adapters, translators, facades, and unit tests.

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Generates Architecture Decision Records (ADR) for PHP projects. Creates structured decision documentation with context, decision, and consequences.

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When the user needs to integrate multiple data sources (Canvas API, user memory, file systems) to create comprehensive academic reports. This skill combines course information, assignment details, submission status, and user context to generate actionable insights. Triggers include requests that involve cross-referencing multiple data sources or creating consolidated academic reports from disparate systems.

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Analyze context and decide on continuation via Stop hook. Use when determining if work should continue, analyzing completion status, making continuation decisions, or implementing the Two-Claude pattern.

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Create handoff packages for session transitions. Use when ending sessions, preparing for continuation, saving session state, or creating resumable context.

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Integration patterns for combining Agent-to-Agent (A2A) Protocol with Model Context Protocol (MCP) for hybrid agent communication. Use when building systems that need both agent-to-agent communication and agent-to-tool integration, implementing composite architectures, or when user mentions A2A+MCP integration, hybrid protocols, or multi-agent tool access.

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Fifth step in building instruction context for codebase

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Fourth step in building instruction context for codebase

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Final step in building instruction context for codebase

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Third step in building instruction context for codebase

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[23] UNDERSTAND. Consult external AI models when internal sources are exhausted. Build quality prompts using Prompt150 formula (Context + Query + Method + Style). Use when Loop150 exhausts internal sources, need real-world precedents, confidence <75%, or require reasoning from specialized AI models.

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Second step in building instruction context for codebase

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在每次回复中使用固定前缀并列出本次实际参考的指令/文件，便于校验是否遵循上下文与规则。

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[22] UNDERSTAND. Deep research from all sources — internal (code, git, logs) AND external (web, docs, best practices). Use when choosing libraries, investigating solutions, understanding legal/technical questions, comparing approaches, or anytime you need comprehensive knowledge from both project context and world knowledge. Triggers on "research", "investigate", "find best approach", "what do others do", "compare options", or complex questions requiring multiple sources.

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See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

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