Claude Skills by thedixitjain

| Use when asked to select chart types for analytics dashboards, choose BI visualizations, or design data displays. Examples: \"best chart for sales data\", \"dashboard visualization for metrics\", \"analytics chart selection\"

Design and spec an analytical dashboard — define the question each chart answers, write the SQL queries, spec the layout and refresh cadence. Produces a complete dashboard spec ready to implement. Use when asked to \"build a dashboard\", \"analytics dashboard\", \"BI dashboard\", \"weekly product health\", or \"visualize this data\".

Analytics reconnaissance for takeover — find all analytics tools, inventory what's tracked and dashboarded, assess data freshness and metric definitions, and present a coverage map. Use when asked \"what analytics exist\", \"BI assessment\", or \"what do we track\".

Build a reporting pipeline — scheduled reports with SQL queries, delivery via Slack or email, threshold alerts, and historical comparison. Use when asked for \"automated reports\", \"scheduled report\", \"email digest\", or \"Slack alerts for metrics\".

Analytics and BI engineer — dashboards, metrics design, reporting pipelines, and data storytelling.

Check for active liens and theft records on a vehicle by VIN using the CarsXE API. Use this when a user asks whether a car has a lien, is stolen, or wants to verify ownership is clean before buying.

'Build and configure multi-step Lindy AI agent workflows. Use when creating agents with triggers, actions, conditions, knowledge bases, or agent steps. Trigger with phrases like \"create lindy agent\", \"build lindy agent\", \"lindy agent workflow\", \"configure lindy agent\", \"lindy workflow\". '

'Configure Lindy triggers, scheduling, multi-agent delegation, and automation. Use when setting up trigger-based workflows, scheduling agents, building multi-agent societies, or configuring agent delegation. Trigger with phrases like \"lindy automation\", \"schedule lindy agent\", \"lindy workflow automation\", \"lindy delegation\", \"lindy multi-agent\". '

'Optimize Lindy AI costs through credit management, model selection, and agent consolidation. Use when reducing spend, analyzing credit usage patterns, or optimizing budget allocation across agents. Trigger with phrases like \"lindy cost\", \"lindy billing\", \"reduce lindy spend\", \"lindy budget\", \"lindy credits\". '

'Create your first Lindy AI agent with a real trigger and action. Use when starting with Lindy, testing your setup, or learning basic agent workflow patterns. Trigger with phrases like \"lindy hello world\", \"lindy example\", \"lindy quick start\", \"simple lindy agent\", \"first lindy\". '

'Configure Lindy AI across development, staging, and production environments. Use when setting up isolated workspaces, per-environment secrets, or environment-specific agent configurations. Trigger with phrases like \"lindy environments\", \"lindy staging\", \"lindy dev prod\", \"lindy environment setup\", \"lindy workspace isolation\". '

List active session overrides scoped to the caller's tenant — useful for auditing dangling overrides or confirming an override is in effect before retrying

Surface the user's recent AxonFlow governance decisions — answers \"what just got blocked\", \"show me my recent denials\", or feeds a decision-history forensic flow

Control and verify a running Unity Editor with the low-token hera-agent-unity CLI.

Use this skill whenever a request involves a Godot project's live editor or running game: inspect scene, node, or UI state; change scenes, nodes, properties, or signals; run a scene; or prove gameplay or UI behavior. Prefer the `hera` CLI over guessing from project files or stale editor state.

You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natur

You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.

> Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.

Security patterns for autonomous trading agents with wallet or transaction authority. Covers prompt injection, spend limits, pre-send simulation, circuit breakers, MEV protection, and key handling.

具有钱包或交易权限的自主交易代理的安全模式。涵盖提示注入、支出限制、发送前模拟、断路器、MEV保护和密钥处理。

日本語翻訳：このファイルは llm-trading-agent-security 用の日本語翻訳が必要です

Register ICANN domains with crypto payments (USDC/USDT/ETH/BTC) via API — built for AI agents

Activez cette compétence lorsqu'un apprenant souhaite : - Exécuter un agent entièrement en local pour des raisons de confidentialité, de coût ou d'utilisation hors connexion. - Servir un modèle localement avec Foundry Local et se connecter via un endpoint compatible OpenAI. - Utiliser un modèle Qwen fonction-appel pour piloter des appels d'outils locaux fiables. - Ajouter un RAG local (Chroma) ou un serveur MCP local.

הפעל מיומנות זו כאשר לומד רוצה: - להריץ סוכן מלא במכשיר למען פרטיות, עלות או סיבות לא מקוונות. - להפעיל מודל מקומית עם Foundry Local ולחבר דרך נקודת קצה התומכת ב-OpenAI. - להשתמש במודל Qwen קריאת-פונקציות כדי להניע קריאות כלים מקומיות אמינות. - להוסיף RAG מקומי (Chroma) או שרת MCP מקומי. - לתכנן אסטרטגיית ניתוב היברידית בין מקומי/ענן.

Aktifkan keterampilan ini ketika pelajar ingin: - Menjalankan agen sepenuhnya di perangkat untuk alasan privasi, biaya, atau offline. - Menyajikan model secara lokal dengan Foundry Local dan terhubung melalui endpoint kompatibel OpenAI. - Menggunakan model pemanggilan fungsi Qwen untuk menjalankan panggilan alat lokal yang andal. - Menambahkan RAG lokal (Chroma) atau server MCP lokal.

Attiva questa competenza quando un apprendente vuole: - Eseguire un agente completamente sul dispositivo per motivi di privacy, costo o offline. - Servire un modello localmente con Foundry Local e connettersi tramite l'endpoint compatibile OpenAI. - Usare un modello Qwen per chiamata di funzioni per guidare chiamate affidabili a strumenti locali. - Aggiungere RAG locale (Chroma) o un server MCP locale.

학습자가 다음을 원할 때 이 스킬을 활성화하세요: - 완전히 기기 내에서 에이전트를 실행하여 개인 정보 보호, 비용 절감 또는 오프라인 목적을 달성. - <strong>Foundry Local</strong>을 사용하여 로컬에서 모델 서비스를 제공하고 OpenAI 호환 엔드포인트로 연결. - 신뢰할 수 있는 로컬 도구 호출을 위해 Qwen 함수 호출 모델 사용. - 로컬 RAG (Chroma) 또는 로컬 MCP 서버 추가. - <strong>하이브리드</strong> 로컬/클라우드 라우팅 전략 설계.

Aktyvinkite šią įgūdį, kai besimokantis nori: - Vykdyti agentą visiškai įrenginyje dėl privatumo, sąnaudų ar neprisijungimo priežasčių. - Vietoje aptarnauti modelį naudojant Foundry Local ir prisijungti per OpenAI suderinamą galutinį tašką. - Naudoti Qwen funkcijų kvietimo modelį patikimam vietiniam įrankių kvietimui. - Pridėti vietinį RAG (Chroma) arba vietinį MCP serverį. - Sukurti hibridinę vietinės/debesijos maršruto strategiją.

जेव्हा एखाद्या शिकणाऱ्याला खालीलप्रमाणे करायचं असेल तेव्हा हे कौशल्य सक्रिय करा: - गोपनीयता, खर्च किंवा ऑफलाइन कारणांसाठी एजंट पूर्णपणे डिव्हाइसवर चालवा. - Foundry Local सह मॉडेल स्थानिक स्वरूपात चालवा आणि OpenAI-सुसंगत एंडपॉइंटद्वारे कनेक्ट करा. - विश्वासार्ह स्थानिक टूल कॉलसाठी Qwen फंक्शन-कॉलिंग मॉडेल वापरा. - स्थानिक RAG (Chroma) किंवा स्थानिक MCP सर्व्हर जोडा. - हायब्रिड स्थानिक/क्लाउड रूटिंग धोरण डिझाइन करा.

Aktifkan kemahiran ini apabila pelajar mahu: - Menjalankan ejen sepenuhnya di peranti untuk privasi, kos, atau sebab luar talian. - Menyediakan model secara tempatan dengan Foundry Local dan sambungkan melalui titik akhir sepadan OpenAI. - Menggunakan model Qwen pemanggil fungsi untuk menggerakkan panggilan alat tempatan yang boleh dipercayai. - Menambah RAG tempatan (Chroma) atau pelayan MCP tempatan.

Aktiver denne ferdigheten når en lærer ønsker å: - Kjøre en agent helt på enheten for personvern, kostnad eller offline grunner. - Tjene en modell lokalt med Foundry Local og koble til via OpenAI-kompatibelt endepunkt. - Bruke en Qwen-funksjonskall-modell for å drive pålitelige lokale verktøysanrop. - Legge til lokal RAG (Chroma) eller en lokal MCP-server. - Designe en hybrid lokal/sky rutingsstrategi.

'Build local-first AI agents wey dey run fully for developer workstation wit Microsoft Foundry Local and Qwen function-calling models. E cover Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG wit Chroma, local MCP servers, hybrid cloud/local routing, and di privacy/cost/offline trade-offs. E based on Lesson 17 of AI Agents for Beginners. USE FOR: run agent locally, offline agent, on-device agent, Foundry Local, Qwen function calling, local t...

Активирайте това умение, когато учащ иска да: - Стартира агент изцяло на устройството по причини за поверителност, разходи или офлайн работа. - Служи на модел локално с Foundry Local и да се свърже чрез OpenAI-съвместим крайна точка. - Използва Qwen модел с извикване на функции за надеждно локално извикване на инструменти. - Добави локален RAG (Chroma) или локален MCP сървър. - Проектира хибридна локална/облачна стратегия за маршрутизиране.

Aktywuj tę umiejętność, gdy uczeń chce: - Uruchomić agenta w pełni na urządzeniu ze względów prywatności, kosztów lub pracy offline. - Udostępnić model lokalnie za pomocą Foundry Local i połączyć się przez zgodny z OpenAI punkt końcowy. - Użyć modelu Qwen z wywoływaniem funkcji do niezawodnego lokalnego wywoływania narzędzi. - Dodać lokalne RAG (Chroma) lub lokalny serwer MCP. - Zaprojektować hybrydową strategię trasowania lokalnego/chmurowego.

Ative essa habilidade quando um aprendiz quiser: - Rodar um agente totalmente no dispositivo por motivos de privacidade, custo ou offline. - Servir um modelo localmente com Foundry Local e conectar via endpoint compatível com OpenAI. - Usar um modelo de chamada de função Qwen para conduzir chamadas confiáveis a ferramentas locais. - Adicionar RAG local (Chroma) ou um servidor MCP local.

Ative esta competência quando um aluno quiser: - Executar um agente totalmente no dispositivo por razões de privacidade, custo ou offline. - Servir um modelo localmente com Foundry Local e conectar via o endpoint compatível com OpenAI. - Usar um modelo Qwen de chamada de funções para conduzir chamadas confiáveis a ferramentas locais. - Adicionar RAG local (Chroma) ou um servidor MCP local.

Activează această competență când un cursant dorește să: - Ruleze un agent complet pe dispozitiv pentru motive de confidențialitate, cost sau offline. - Servească un model local cu Foundry Local și se conecteze prin endpoint-ul compatibil OpenAI. - Folosească un model de apelare a funcțiilor Qwen pentru a genera apeluri de instrumente locale fiabile. - Adauge RAG local (Chroma) sau un server MCP local.

Активируйте это умение, когда ученик хочет: - Запустить агента полностью на устройстве ради конфиденциальности, экономии или офлайн-режима. - Обслуживать модель локально с помощью Foundry Local и подключаться через OpenAI-совместимый эндпоинт. - Использовать модель с функциональным вызовом Qwen для надежных локальных вызовов инструментов. - Добавить локальный RAG (Chroma) или локальный MCP сервер.

Aktivujte túto zručnosť, keď chce študent: - Spustiť agenta úplne na zariadení z dôvodu ochrany súkromia, nákladov alebo offline prevádzky. - Poskytnúť model lokálne pomocou Foundry Local a pripojiť sa prostredníctvom endpointu kompatibilného s OpenAI. - Použiť model Qwen s volaním funkcií na riadenie spoľahlivých lokálnych volaní nástrojov. - Pridať lokálny RAG (Chroma) alebo lokálny MCP server.

Aktiviraj to veščino, ko učenec želi: - Zagnati agenta popolnoma na napravi zaradi zasebnosti, stroškov ali brez povezave. - Postreči model lokalno z Foundry Local in se povezati prek OpenAI združljivega konektorja. - Uporabiti model Qwen za klicanje funkcij za zanesljive lokalne klice orodij. - Dodati lokalni RAG (Chroma) ali lokalni MCP strežnik. - Oblikovati hibridno usmerjevalno strategijo lokalno/oblak.

Активирајте ову вештину када ученик жели да: - Покрене агента у потпуности локално због приватности, трошкова или рада без мреже. - Сервира модел локално помоћу Foundry Local и повезује се преко OpenAI-совместивог крајњег тачку. - Користи модел за Qwen позив функција да поуздано покреће локалне позиве алата. - Дода локални RAG (Chroma) или локални MCP сервер. - Дизајнира хибридну локалну/облачну стратегију рутирања.

Aktivera denna färdighet när en lärande vill: - Köra en agent helt på enheten för integritet, kostnad eller offline-anledningar. - Servera en modell lokalt med Foundry Local och anslut via OpenAI-kompatibel endpoint. - Använda en Qwen funktionsanropsmodell för att driva pålitliga lokala verktygsanrop. - Lägga till lokal RAG (Chroma) eller en lokal MCP-server. - Designa en hybrid lokal/molnruttstrategi.

Wekeza ujuzi huu wakati mjuzi anataka: - Endesha ajenti kizima kabisa kwenye kifaa kwa sababu za faragha, gharama, au matumizi bila mtandao. - Hudumia mfano wa ndani kwa Foundry Local na unganisha kupitia kiungo kinacholingana na OpenAI. - Tumia mfano wa Qwen unaoitisha kazi kuendesha kwa uhakika kuitishwa kwa zana za ndani. - Ongeza RAG ya ndani (Chroma) au seva ya MCP ya ndani. - Buni mkakati wa mseto wa mipangilio ya mawasiliano ya ndani/wingi.

Aktivujte tuto dovednost, když učenec chce: - Spustit agenta zcela na zařízení kvůli ochraně soukromí, nákladům nebo offline provozu. - Poskytovat model lokálně pomocí Foundry Local a připojit se přes OpenAI-kompatibilní endpoint. - Použít model Qwen s voláním funkcí k spolehlivému lokálnímu volání nástrojů. - Přidat lokální RAG (Chroma) nebo lokální MCP server. - Navrhnout hybridní strategii směrování mezi lokálním a cloudovým modelem.

เปิดใช้งานทักษะนี้เมื่อผู้เรียนต้องการ: - รันเอเจนต์ ทั้งหมดบนอุปกรณ์ เพื่อความเป็นส่วนตัว ต้นทุน หรือเหตุผลการทำงานแบบออฟไลน์ - ให้บริการโมเดลในเครื่องด้วย Foundry Local และเชื่อมต่อผ่านจุดสิ้นสุดที่เข้ากันได้กับ OpenAI - ใช้โมเดล Qwen ที่เรียกใช้งานฟังก์ชัน เพื่อขับเคลื่อนการเรียกใช้เครื่องมือในเครื่องอย่างเชื่อถือได้ - เพิ่ม local RAG (Chroma) หรือ เซิร์ฟเวอร์ MCP ในเครื่อง - ออกแบบกลยุทธ์การจัดเส้นทางแบบ ไฮบริด ระหว่างท้องถิ่น/คลาวด์

'Bumuo ng mga local-first AI agents na tumatakbo nang buong-buo sa isang developer workstation gamit ang Microsoft Foundry Local at Qwen function-calling models. Saklaw nito ang Small Language Models (SLMs), ang OpenAI-compatible na lokal na endpoint, sandboxed local tools, lokal na RAG gamit ang Chroma, lokal na MCP servers, hybrid cloud/local routing, at ang privacy/cost/offline trade-offs. Batay sa Lesson 17 ng AI Agents for Beginners. GAMITIN PARA SA: pagpapatakbo ng agent nang lokal, off...

Активуйте цю навичку, коли навчальний хоче: - Запустити агента повністю на пристрої з міркувань конфіденційності, вартості або автономної роботи. - Обслуговувати модель локально за допомогою Foundry Local та підключатися через сумісну з OpenAI точку доступу. - Використовувати модель Qwen з функцією виклику, щоб забезпечити надійні локальні виклики інструментів. - Додати локальний RAG (Chroma) або локальний MCP сервер.

Kích hoạt kỹ năng này khi người học muốn: - Chạy một đại lý hoàn toàn trên thiết bị vì lý do riêng tư, chi phí hoặc khi ngoại tuyến. - Phục vụ một mô hình cục bộ với Foundry Local và kết nối qua điểm cuối tương thích OpenAI. - Sử dụng mô hình Qwen gọi hàm để điều khiển cuộc gọi công cụ cục bộ đáng tin cậy. - Thêm RAG cục bộ (Chroma) hoặc máy chủ MCP cục bộ. - Thiết kế chiến lược định tuyến lai cục bộ/đám mây.

当学习者希望： - 由于隐私、成本或离线需求而<strong>完全在设备上运行</strong>代理时。 - 使用 Foundry Local 在本地部署模型，并通过 OpenAI 兼容端点进行连接。 - 使用 <strong>Qwen 函数调用</strong>模型来驱动可靠的本地工具调用时。 - 添加 本地 RAG（Chroma）或 本地 MCP 服务器。 - 设计一个<strong>混合型</strong>本地/云路由策略。

學習者希望在以下情況下啟動此技能： - 完全<strong>在設備上運行</strong>代理，考慮到隱私、成本或離線需求。 - 使用 Foundry Local 於本地提供模型，並通過 OpenAI 相容端點連接。 - 使用 <strong>Qwen 函數調用</strong>模型驅動可靠的本地工具調用。 - 添加 本地 RAG（Chroma）或 本地 MCP 服務器。 - 設計 <strong>混合</strong> 本地/雲端路由策略。