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Found 1,592 Skills
Motoko language pitfalls and modern syntax for the Internet Computer. Covers persistent actor requirements, stable types, mo:core standard library, type system rules, and common compilation errors. Use when writing Motoko canister code, fixing Motoko compiler errors, or generating Motoko actors. Do NOT use for deployment, icp.yaml config, or CLI commands — use icp-cli instead. Do NOT use for upgrade persistence patterns — use stable-memory instead.
Composes, debugs, and optimizes Guillotine GraphQL queries for Enonic XP headless content delivery. Covers query construction, variable usage, filtering, aggregation, pagination, sorting, and TypeScript type generation from the auto-generated Guillotine schema. Use when writing or troubleshooting Guillotine queries, querying custom content types through GraphQL, or generating typed interfaces from Guillotine responses. Don't use for content type XML definitions, non-Enonic GraphQL APIs (Apollo, Hasura), server-side lib-content queries, or Guillotine deployment and CORS configuration.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for AI-agent, prompt-injection, MCP or toolchain, cloud, container, CI/CD, and supply-chain challenges. Use when the user asks to analyze prompt-to-tool flows, retrieval poisoning, mounted secrets, deployment drift, runtime-vs-manifest mismatches, registry provenance, or CI-produced artifacts under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Salesforce Industries CME EPC product-modeling skill for Product2-based catalog creation. Use when creating EPC products, configuring product attributes, building offer bundles with Product Child Items, or reviewing EPC DataPack JSON metadata for product catalog changes. TRIGGER when: user creates or updates Product2 EPC records, AttributeAssignment payloads, AttributeMetadata/AttributeDefaultValues, Offer bundles, or ProductChildItem relationships. DO NOT TRIGGER when: designing OmniScripts/FlexCards/Integration Procedures (use sf-industry-commoncore-* skills), implementing Apex business logic (use sf-apex), or troubleshooting deployment pipelines (use sf-deploy).
Use when planning or reviewing production database migrations, adding columns, indexes, constraints, backfills, renames, table rewrites, or concurrent operations. Covers phased rollouts, lock behavior, rollback strategy, strong_migrations compliance, and deployment ordering for schema changes.
The Twelve-Factor App methodology for building scalable, maintainable cloud-native applications. Use when designing backend services, APIs, microservices, or any software-as-a-service application. Triggers on deployment patterns, configuration management, process architecture, logging, and infrastructure decisions.
This skill should be used when the user asks to "build background agent", "create hosted coding agent", "set up sandboxed execution", "implement multiplayer agent", or mentions background agents, sandboxed VMs, agent infrastructure, Modal sandboxes, self-spawning agents, or remote coding environments. Part of the context engineering skill suite — also activates when the user mentions "context engineering" or "context-engineering" in the context of agent deployment and execution infrastructure.
Apply AI ethics frameworks (fairness, accountability, transparency, privacy) to evaluate AI systems for algorithmic bias, explainability gaps, and value alignment failures. Use this skill when the user needs to audit an AI system for ethical risks, design fairness constraints, assess explainability requirements, or when they ask 'is this AI system fair', 'how do we detect algorithmic bias', 'what are the ethical implications of this AI deployment', or 'how do we make this model explainable to stakeholders'.
昇腾（Ascend）推理生态开源代码仓库智能问答专家旨在为 vLLM、vLLM-Ascend、MindIE-LLM、MindIE-SD、MindIE-Motor、MindIE-Turbo 以及 msModelSlim (MindStudio-ModelSlim) 等仓库提供专家级且易于理解的解释。在处理昇腾（Ascend）推理生态相关项目的用户询问时，务必触发此技能（Skill），可解答使用方法、部署流程、支持模型、支持特性、系统架构、配置管理、调试、测试、故障排查、性能优化、定制开发、源码解析以及其他技术问题。支持中英文双语回复，并可借助 deepwiki MCP 工具检索仓库知识库，生成具备上下文感知且基于证据的回答。Ascend inference ecosystem open-source code repository intelligent question-and-answer (Q&A) expert. Provide expert-level yet comprehensible explanations for repositories such as vLLM, vLLM-Ascend, MindIE-LLM, MindIE-SD, MindIE-Motor, MindIE-Turbo, and msModelSlim (MindStudio-ModelSlim). Use this skill when addressing user inquiries related to these Ascend inference ecosystem projects, including topics such as usage, deployment process, supported models, supported features, system architecture, configuration management, debugging, testing, troubleshooting, performance optimization, custom development, source code analysis, and any other technical issues about these projects. Support responses in both Chinese and English. Use deepwiki MCP tools to query repository knowledge bases and generate context-aware, evidence-based responses.
Expert bash/shell scripting system across ALL platforms. PROACTIVELY activate for: (1) ANY bash/shell script task, (2) System automation, (3) DevOps/CI/CD scripts, (4) Build/deployment automation, (5) Script review/debugging, (6) Converting commands to scripts. Provides: Google Shell Style Guide compliance, ShellCheck validation, cross-platform compatibility (Linux/macOS/Windows/containers), POSIX compliance, security hardening, error handling, performance optimization, testing with BATS, and production-ready patterns. Ensures professional-grade, secure, portable scripts every time.
Grafana Beyla eBPF auto-instrumentation for application observability without code changes. Covers supported languages/runtimes, requirements, installation, configuration (discovery, eBPF settings, OTLP traces export, Prometheus metrics export), Kubernetes deployment, and integration with Grafana Cloud. Use when setting up zero-code instrumentation, configuring eBPF probes, deploying Beyla to Kubernetes, connecting to Tempo/Prometheus, or troubleshooting instrumentation issues.
Grafana Mimir scalable long-term metrics storage. Covers architecture (distributor/ingester/compactor/querier/ query-frontend/store-gateway/ruler), deployment modes (monolithic/microservices), configuration, Prometheus remote write, PromQL querying, multi-tenancy, compaction, and operations. Use when working with Mimir for metrics storage, scaling Prometheus, configuring Mimir clusters, writing PromQL, or debugging Mimir.