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Found 324 Skills
Performs semantic code intelligence and token optimization through context engineering and automated context packing. Use when reducing token overhead for large codebases, creating repository digests with Gitingest, packaging code context with Repomix, or tracing cross-file dependencies with llm-tldr.
Full Sentry SDK setup for NestJS. Use when asked to "add Sentry to NestJS", "install @sentry/nestjs", "setup Sentry in NestJS", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for NestJS applications. Supports Express and Fastify adapters, GraphQL, microservices, WebSockets, and background jobs.
Set up comprehensive observability for Instantly integrations with metrics, traces, and alerts. Use when implementing monitoring for Instantly operations, setting up dashboards, or configuring alerting for Instantly integration health. Trigger with phrases like "instantly monitoring", "instantly metrics", "instantly observability", "monitor instantly", "instantly alerts", "instantly tracing".
Expert guidance for Django REST Framework class-based views using Classy DRF (https://www.cdrf.co). Use when selecting or debugging APIView, GenericAPIView, concrete generic views, mixin combinations, or ViewSet/GenericViewSet/ModelViewSet behavior; tracing method resolution order (MRO); understanding which method to override (`create` vs `perform_create`, `update` vs `perform_update`, `destroy` vs `perform_destroy`, `get_queryset`, `get_serializer_class`); and comparing behavior across DRF versions. Do not use for function-based views, GraphQL, FastAPI/Flask, frontend work, or non-DRF backend frameworks.
Salesforce Data Cloud Retrieve phase. TRIGGER when: user runs Data Cloud SQL, describe, async queries, vector search, search-index workflows, or metadata introspection for Data Cloud objects. DO NOT TRIGGER when: the task is standard CRM SOQL (use sf-soql), segment creation or calculated insight design (use sf-datacloud-segment), or STDM/session tracing/parquet analysis (use sf-ai-agentforce-observability).
Salesforce Data Cloud Harmonize phase. TRIGGER when: user works with DMOs, mappings, relationships, identity resolution, unified profiles, data graphs, or universal IDs. DO NOT TRIGGER when: the task is only about streams/DLOs (use sf-datacloud-prepare), segments/insights (use sf-datacloud-segment), retrieval/search (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
Salesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
Salesforce Data Cloud Act phase. TRIGGER when: user manages activations, activation targets, data actions, or downstream delivery of Data Cloud audiences and data. DO NOT TRIGGER when: the task is segment creation (use sf-datacloud-segment), data retrieval/search work (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
Analyze MSBuild binary logs to diagnose build failures by replaying binlogs to searchable text logs. Only activate in MSBuild/.NET build context. USE FOR: build errors that are unclear from console output, diagnosing cascading failures across multi-project builds, tracing MSBuild target execution order, investigating common errors like CS0246 (type not found), MSB4019 (imported project not found), NU1605 (package downgrade), MSB3277 (version conflicts), and ResolveProjectReferences failures. Requires an existing .binlog file. DO NOT USE FOR: generating binlogs (use binlog-generation), build performance analysis (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: dotnet msbuild binlog replay, grep, cat, head, tail for log analysis.
Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing. Includes AI-friendly log formats for Claude Code debugging. Use when user asks about logging, debugging application flow, or analyzing logs.
Generate 3D CGI and rendered video prompts for Seedance 2.0 (Higgsfield). Use this when users want 3D rendering, CGI, Pixar-style, Unreal Engine, photorealistic 3D, computer-generated, or digitally rendered video content. Trigger words: 3D animation, CGI, rendering, Blender, Unreal Engine, octane render, ray tracing, volume, subsurface scattering, physically based rendering, or any 3D/CG video request. Use this even if the user only says "make it look 3D" or describes a rendering aesthetic.
Use the unified Opper SDKs (`opperai` package for both Python and TypeScript, with built-in agent support) for AI task completion, structured output with Pydantic / Zod / JSON Schema, knowledge base semantic search, streaming, tracing, tool use, and multi-agent composition. Use this skill whenever the user is writing Python or TypeScript code that imports `opperai`, builds an Opper agent, or asks how to do anything Opper-related in code — even if they don't explicitly name the SDK. Both languages live in one repo with parallel numbered examples; agents are part of the SDK, not a separate package.