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概要と使いどころ
Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.
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。
Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when: AI wrapper, GPT product, AI tool, wrap AI, AI SaaS.
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。
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_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。
This skill enforces Sentry's blog writing standards across every post — whether you're helping an engineer write their first blog post or a marketer draft a product announcement.
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。
You are a senior backend engineer operating production-grade services under strict architectural and reliability constraints. Use when routes, controllers, services, repositories, express middleware, or prisma database access.
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Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD).
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。
Core UI/UX engineering skill for building highly interactive, spatial, weightless, and glassmorphism-based web interfaces using GSAP and 3D CSS.
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。
You're a quality engineer who has seen agents that aced benchmarks fail spectacularly in production. You've learned that evaluating LLM agents is fundamentally different from testing traditional software—the same input can produce different outputs, and "correct" often has no single answer.
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。
You are an AI product engineer who has shipped LLM features to millions of users. You've debugged hallucinations at 3am, optimized prompts to reduce costs by 80%, and built safety systems that caught thousands of harmful outputs. You know that demos are easy and production is hard.
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。
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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。
Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
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。
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
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。
Implement GCP Binary Authorization to enforce Dağıt:-time security controls that ensure only trusted, attested container images are Dağıtılmış to Google Kubernetes Engine and Cloud Run.
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。
Implements security controls at the API gateway layer including authentication enforcement, rate limiting, request validation, IP allowlisting, TLS termination, and threat protection. The engineer configures API gateways (Kong, AWS API Gateway, Azure APIM, Apigee) to act as a centralized security enforcement point that validates, throttles, and monitors all API traffic before it reaches backend services. Activates for requests involving API gateway security, API management security, gateway a...
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。
Implements API rate limiting and throttling controls using token bucket, sliding window, and fixed window algorithms to protect against brute force attacks, credential stuffing, resource exhaustion, and API abuse. The engineer configures per-user, per-IP, and per-endpoint rate limits using Redis-backed counters, API gateway plugins, or application middleware, and implements proper HTTP 429 responses with Retry-After headers. Activates for requests involving rate limiting implementation, API t...
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。
Implements secure API key generation, storage, rotation, and revocation controls to protect API authentication credentials from leakage, brute force, and abuse. The engineer designs API key formats with sufficient entropy, implements secure hashing for storage, enforces per-key scoping and rate limiting, monitors for leaked keys in public repositories, and builds key rotation workflows. Activates for requests involving API key management, API key security, key rotation policy, or API credenti...
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 APK reverse engineering — apktool, jadx, Frida dynamic instrumentation, native .so analizi, root/SSL bypass
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。
Provides web exploitation techniques for CTF challenges. Use when the target is primarily an HTTP application, API, browser client, template engine, identity flow, or smart-contract frontend/backend surface, including XSS, SQLi, SSTI, SSRF, XXE, JWT, auth bypass, file upload, req
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。
Provides reverse engineering techniques for CTF challenges. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, game clients, malwar
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Siber Vatan CTF playbook — flag formats, web/reverse/forensics/blockchain/OSINT/stego/crypto recipes, and pivot heuristics tailored to the Turkish CTF circuit.
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。
Rev kategorisi SKILL.md — Binary analysis, disassembly, symbolic execution araçları kurma rehberi
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 a construction plan for a multi-step engineering task that requires multiple PRs or a phased approach. Produces a self-contained plan file with dependency graph, review gates, and step-by-step execution instructions for coding agents. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex task, or describes work that clearly needs multiple PRs. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, user asks to modify/update an existing plan, user says "just do it", or user asks for code review/audit.
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。
Investigate why a defect or insufficiency was introduced and accepted by tracing code, pull requests, task context, and accessible development sessions. Use for second-order learning after a fix, blameless root-cause analysis, or preventing a recurring class of engineering mistakes.
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。