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Bu template'i klonladiktan sonraki tum kurulumu yurutur — bagimliliklar ve codegen, projeyi kendine uyarlama, Firebase, giris yontemleri (Google/Apple/e-posta dogrulama/misafir gezinme), zorunlu guncelleme (Remote Config), odeme ve abonelik (RevenueCat), Android release imzalama (keystore), native splash ve store URL'leri. Kullaniciya ne istedigini sorar, AppConfig bayraklarini cevirir ve Firebase Console / Apple Developer / Play Console / RevenueCat tarafinda yapmasi gerekenleri sirayla listeler. Kullanici "kurulumu yap", "kurulumu baslat", "klonladim ne yapmaliyim", "Firebase'i bagla", "odeme ekle", "keystore olustur", "release imzasi kur", "set up the project" dediginde kullan. Repoyu ilk kez calistiran icin GIRIS NOKTASIDIR.

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Multi-tiered memory management (HOT/WARM/COLD) for context compaction. Invoke ONLY for explicit compaction events: post-`/compact` cleanup, MEMORY.md tier promotion, archive batch, or "trim my context". NOT for general recall (use deep-recall) or routine memory writes (use storage-router). Triggers: "compact memory", "promote to durable", "archive old context", "tier this".

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。

Search past WhatsApp/chat conversations stored in the audit log PostgreSQL database. Use when the user asks about past conversations, what was discussed, what someone said, finding a specific message, or referencing previous discussions. Also use to reply to or quote specific past messages.

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。

Single-skill wrapper for the 4-layer recall (durable memory → semantic DB → PostgreSQL → daily notes). Use BEFORE saying "I don't have context". Triggers: "search memory", "what do we know about X", "deep recall", "I don't remember".

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。

4-layer recall procedure (durable → semantic → PostgreSQL → daily notes) before claiming "no context". Invoke when user explicitly asks "do you remember", "what did we discuss about X", "search history". NOT a general assistant — only fires when recall is the explicit task. Drop the prior "use proactively" rule. Triggers: "do you remember", "what did we discuss", "when did", "find that conversation about".

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。

Use when working with Cast Ai — cAST AI Kubernetes cluster optimization and cost management. Covers cluster cost optimization, spot instance management, cost reports, node rebalancing, security posture, and workload right-sizing. Use when optimizing Kubernetes cluster costs, managing node lifecycle, or analyzing cloud spend with CAST AI.

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Use when working with Aws Inspector — aWS Inspector vulnerability management and finding analysis. Covers Inspector v2 coverage, vulnerability findings, finding summaries, scan configurations, suppression rules, and coverage statistics. Use when auditing vulnerability posture, reviewing Inspector findings, checking scan coverage, or analyzing security vulnerabilities across EC2, ECR, and Lambda resources.

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。

Use when working with Aws Guardduty — aWS GuardDuty finding analysis, detector management, suppression rule review, and member account oversight. Covers threat detection summary, finding severity distribution, finding type breakdown, trusted IP lists, and organization-wide security posture.

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。

Use when working with Kubescape — kubescape Kubernetes security posture analysis. Covers NSA/CISA framework assessment, MITRE ATT&CK mapping, CIS Kubernetes benchmarks, workload scanning, RBAC analysis, and network policy evaluation. Use when assessing Kubernetes cluster security, evaluating compliance frameworks, or analyzing workload configurations.

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。

Use when working with Aqua — aqua Security platform analysis. Covers container runtime protection, image assurance policies, compliance frameworks, vulnerability management, workload protection, and registry scanning. Use when analyzing container security posture, reviewing image compliance, investigating runtime alerts, or auditing security policies.

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 work studies the post-training quantization of LLM parameters as a way to improve their runtime GAP: multi-agent orchestration: competitor signal

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。

Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.

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X (Twitter) Scraper API and X API Alternative instructions for Xquik scraping and connected X account action planning. Also use for Xquik Radar or Xquik support tickets only when the user names that feature. Do not load or use this Skill for official X developer setup unless the user compares it with Xquik. Trigger when an X or Twitter task asks about posts, replies, likes, follows, messages, search, users, timelines, followers, exports, giveaways, draws, monitors, Xquik webhooks, MCP setup, SDKs, or API comparisons. Start read-only. Require confirmation for write plans, private reads, monitors, webhooks, support access, and metered bulk jobs. Not affiliated with X Corp.

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 en cinématographie drone (DJI, planification de vol, réglementations, post-traitement, mapping)

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。

Database optimization v3 — query plans, partitioning, indexing, connection pooling, PostgreSQL, MySQL

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 en optimisation de bases de données (query plans, indexing strategies, partitioning, vacuum)

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。

Generate MSBuild binary logs (binlogs) for build diagnostics and analysis. Only activate in MSBuild/.NET build context. USE FOR: adding /bl:{} to any dotnet build, test, pack, publish, or restore command to capture a full build execution trace, prerequisite for binlog-failure-analysis and build-perf-diagnostics skills, enabling post-build investigation of errors or performance. Requires MSBuild 17.8+ / .NET 8 SDK+ for {} placeholder; PowerShell needs -bl:{{}}. DO NOT USE FOR: non-MSBuild build systems (npm, Maven, CMake), analyzing an existing binlog (use binlog-failure-analysis instead). INVOKES: shell commands (dotnet build /bl:{}).

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。

Validates custom dotnet new templates for correctness before publishing. Catches missing fields, parameter bugs, shortName conflicts, constraint issues, and common authoring mistakes that cause templates to fail silently. USE FOR: checking template.json files for errors before publishing or testing, diagnosing why a template doesn't appear after installation, reviewing template parameter definitions for type mismatches and missing defaults, finding shortName conflicts with dotnet CLI commands, validating post-action and constraint configuration. DO NOT USE FOR: finding or using existing templates (use template-discovery), creating projects from templates (use template-instantiation), creating templates from existing projects (use template-authoring).

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 and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.

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。

Guides creation and validation of custom dotnet new templates. Generates templates from existing projects and validates template.json for authoring issues. USE FOR: creating a reusable dotnet new template from an existing project, validating template.json files for schema compliance and parameter issues, bootstrapping .template.config/template.json with correct identity, shortName, parameters, and post-actions, packaging templates as NuGet packages for distribution. DO NOT USE FOR: finding or using existing templates (use template-discovery and template-instantiation), MSBuild project file issues unrelated to template authoring, NuGet package publishing (only template packaging structure).

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。

Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.

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。

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

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。

Review PR changes against project standards and post feedback

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。

Write and improve prompts for Qwen-Image-2.1, Alibaba's open-weight image generation and editing model. Use whenever the user wants to generate or edit images with Qwen-Image / Qwen-Image-2.1 / Qwen-Image-Edit, asks for help prompting any Qwen image model, needs readable text rendered inside an image (posters, signs, UI mockups, infographics), wants to combine several reference images into one, or asks about aspect ratios, styles, or camera settings for Qwen image generation — even when they are only choosing an image model for a text-heavy graphic and have not named the model yet.

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。