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Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로.
Builds, tests, and deploys Microsoft 365 apps and agents for Teams and Copilot. Includes sub-skills for project creation, local testing, cloud deployment, troubleshooting, and Slack-to-Teams migration. USE FOR: Teams agent, bot, tab, message extension, Declarative Agents, Custom Engine Agents, local testing, Agents Playground, Azure resource provision, remote deployment, Slack to Teams migration, cross-platform bot development, Block Kit to Adaptive Cards conversion. DO NOT USE FOR: general web development, non-bot/non-Teams projects.
Out-of-core DataFrame for billion-row data via lazy evaluation and memory-mapped files. Use when data exceeds RAM (10 GB–TB) for fast aggregation, filtering, virtual columns, and visualization without loading. Supports HDF5, Arrow, Parquet, CSV with cloud (S3, GCS, Azure). Built-in ML transformers (scaling, PCA, K-means). In-memory: polars; distributed: dask.
Build, manage, and operate APIs with Amazon API Gateway (REST, HTTP, and WebSocket). Triggers on phrases like: API Gateway, REST API, HTTP API, WebSocket API, custom domain, Lambda authorizer, usage plan, throttling, CORS, VPC link, private API. Also covers troubleshooting API Gateway errors (4xx, 5xx, timeout, CORS failures) and IaC templates containing API Gateway resources. For general REST API design unrelated to AWS, do not trigger.
Use this skill when migrating a Phaser 3 project to Phaser 4, or when a user asks about breaking changes, API differences, or how to update their v3 code. Covers renderer changes (pipelines to render nodes), FX/masks to filters, tint system, camera matrix, texture coordinates, DynamicTexture, shaders, lighting, removed game objects, and a full migration checklist. Triggers on: migrate, upgrade, v3 to v4, breaking changes, Phaser 3 to 4, migration guide, update from v3.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three-way literature scan, 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, WHY HOW WHAT papers, 3W literature scan, 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, 三段式文獻掃描, 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, 심층 연구, 문헌 조사, 체계적 문헌고찰, 메타분석, 사실 확인, 연구 방향을 잡아줘, 연구 주제 정하는 것을 도와줘.
Security hardening reviewer for GitHub Actions workflow files (.github/workflows/*.yml). Reasons about the Actions threat model that pattern matchers and general code linters miss — untrusted-input script injection, privileged triggers running fork code, mutable action references, and over-scoped tokens. Use this skill when asked to review, audit, harden, or secure a GitHub Actions workflow, when writing a new workflow, or for any request like "is this workflow safe?", "review my CI for security issues", "why is pull_request_target dangerous here?", "pin my actions", or "lock down GITHUB_TOKEN permissions". Covers script injection via ${{ }} interpolation, pull_request_target / workflow_run privilege escalation, SHA-pinning of third-party actions, least-privilege permissions, GITHUB_ENV/GITHUB_OUTPUT injection, secret exposure, OIDC over long-lived credentials, and self-hosted runner exposure on public repositories.
Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services
AI-native GRC (Governance, Risk, and Compliance) for OpenClaw. 97 actions across 13 frameworks including SOC 2, ISO 27001, HIPAA, GDPR, NIST CSF, PCI DSS, CIS Controls, CMMC, HITRUST, CCPA, FedRAMP, ISO 42001, and SOX ITGC. Manages controls, evidence, risks, policies, vendors, incidents, assets, training, vulnerabilities, access reviews, and questionnaires. Generates compliance scores, reports, dashboards, and trust center pages. Runs security header, SSL, and GDPR scans. Connects to AWS, Azure, GCP, GitHub, and identity providers via companion skills.
Prepare Azure apps for deployment (infra Bicep/Terraform, azure.yaml, Dockerfiles). Use for create/modernize or create+deploy; not cross-cloud migration (use azure-cloud-migrate). WHEN: "create app", "build web app", "create API", "create serverless HTTP API", "create frontend", "create back end", "build a service", "modernize application", "update application", "add authentication", "add caching", "host on Azure", "create and deploy", "deploy to Azure", "deploy to Azure using Terraform", "deploy to Azure App Service", "deploy to Azure App Service using Terraform", "deploy to Azure Container Apps", "deploy to Azure Container Apps using Terraform", "generate Terraform", "generate Bicep", "function app", "timer trigger", "service bus trigger", "event-driven function", "containerized Node.js app", "social media app", "static portfolio website", "todo list with frontend and API", "prepare my Azure application to use Key Vault", "managed identity".
Skill do analizy i tworzenia umów według polskiego prawa, ze szczególnym uwzględnieniem umów B2B, IP i IT (body leasing, NDA, wdrożenia, SaaS, przeniesienie praw autorskich, ugody). Powstał w Kancelarii Radców Prawnych Żurawska Piotrowski i Wspólnicy (ktzr.pl). Używaj zawsze gdy użytkownik prosi o przeanalizowanie polskiej umowy, audyt ryzyk umownych, wygenerowanie nowej umowy w stylu KTZR, dodanie/edycję klauzuli, sprawdzenie spójności umowy lub gdy wkleja/załącza polski dokument umowny do oceny. Stosuj również gdy pojawia się pojęcie "Złote Reguły KTZR", "essentialia negotii", "baza klauzul KTZR" lub gdy użytkownik wspomina o kancelarii KTZR / swojej kancelarii.
Deploy a production self-hosted n8n end-to-end to a fresh Linux VM over SSH, using Docker Compose behind a Caddy reverse proxy with automatic HTTPS. Use whenever the user wants to self-host, install, set up, provision, or deploy n8n on their own server/VPS/box (Hetzner, DigitalOcean, AWS EC2, bare metal, etc.) — in either single/regular mode or queue mode with workers — or to update, back up, restore, or harden such an instance. This is for SELF-HOSTED n8n (Docker), not n8n Cloud and not building workflows. The skill makes the agent ask single-vs-queue first, collect the domain/SSH/timezone inputs, generate fresh secrets on the box, and bring the stack up with TLS. Trigger on "deploy n8n", "self-host n8n", "install n8n on my server", "n8n docker compose", "n8n queue mode / workers / scaling", "n8n reverse proxy / SSL", or "back up / update my n8n".
Use when working with Lightdash YAML files, dbt models with Lightdash metadata, the lightdash CLI (deploy, upload, download, preview, lint, sql, set-warehouse), or creating/editing charts, dashboards, metrics, and dimensions as code
Deploy and operate Node, Python, Go, Rust, Elixir, and Docker apps on Fly.io with production-grade fly.toml authoring, Machines API orchestration, region selection (latency vs sovereignty vs egress), Fly Postgres clustering, LiteFS for SQLite replication, Upstash Redis bindings, Tigris object storage, persistent volumes, WireGuard private networking with 6PN, secrets via flyctl, blue/green deploys via auto-stopping machines, scale-to-zero strategies, scheduled scaling, preview deploys per PR, multi-region replicas, hot-config reload, machine SSH, log shipping to Better Stack/Axiom/Datadog/Logtail, and aggressive cost tuning. Triggers on "fly.io", "flyctl", "fly machines", "fly.toml", "fly postgres", "litefs", "tigris", "upstash on fly", "fly deploy", "migrate from heroku", "migrate from render", "migrate from railway", "scale to zero", "fly regions", "fly volumes", "fly wireguard", "6pn", "fly secrets".
Assess and migrate cross-cloud workloads to Azure with reports and code conversion. Supports Lambda→Functions, Beanstalk/Heroku/App Engine→App Service, Fargate/Kubernetes/Cloud Run/Spring Boot→Container Apps. WHEN: migrate Lambda to Functions, AWS to Azure, migrate Beanstalk, migrate Heroku, migrate App Engine, Cloud Run migration, Fargate to ACA, ECS/Kubernetes/GKE/EKS to Container Apps, Spring Boot to Container Apps, cross-cloud migration.
Game lifecycle orchestrator: scaffold, assets, audio, QA, deploy.
Export a promoted fine-tuned model in the right deployment format — merged safetensors, LoRA-only, GGUF with imatrix, or FP8. Use after a checkpoint passes promotion, when choosing a quantization format for a target device, or when an exported model fails its smoke test.
Build Model Context Protocol (MCP) servers in C#/.NET against the current ModelContextProtocol 1.x NuGet packages. Especially helps with cases the model often gets wrong without guidance — stale preview versions (it tends to pick 0.3 or 0.4 preview), MCP Apps (interactive UI rendered in the host), elicitation URL mode, per-session HTTP wiring, OAuth and reverse-proxy deploy specifics, and debugging concrete MapMcp / STDIO / Streamable-HTTP errors. Also covers the routine work — STDIO and Streamable HTTP transports (SSE is deprecated), tools, prompts, resources, sampling, roots, completions, logging — and a basic .NET MCP client. Trigger when the user says or implies any .NET MCP server work: ModelContextProtocol, McpServerTool, MapMcp, WithStdioServerTransport, "MCP server in C#", "MCP tool in dotnet", "expose this as MCP", or names a primitive (prompt/resource/elicitation/MCP App) in a .NET context. Skip for MCP work in other languages.
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
Turborepo monorepo build system guidance for turbo.json, task pipelines, dependsOn, caching, remote cache, the turbo CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure, best practices, and boundaries. Use when user configures tasks, workflows, pipelines, creates packages, sets up monorepo, shares code between apps, runs changed or affected packages, debugs cache, or has apps/packages directories.
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