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Found 1,660 Skills
Runs .NET tests with dotnet test. Use when user says "run tests", "execute tests", "dotnet test", "test filter", "tests not running", or needs to detect the test platform (VSTest or Microsoft.Testing.Platform), identify the test framework, apply test filters, or troubleshoot test execution failures. Covers MSTest, xUnit, NUnit, and TUnit across both VSTest and MTP platforms. DO NOT USE FOR: writing or generating test code, CI/CD pipeline configuration, or debugging failing test logic.
Develop the Stitch SDK. Covers the generation pipeline, dual modality (agent vs SDK), error handling, and Traffic Light (Red-Green-Yellow) implementation workflow. Use when adding features, fixing bugs, or understanding the architecture.
MUST USE for any task involving the dotenvx CLI tool — encrypting .env files, running commands with injected env vars, managing secrets across environments, and decrypting at runtime. Use this skill whenever the user mentions dotenvx, dotenv encryption, DOTENV_PRIVATE_KEY, encrypted .env files, or the dotenvx encrypt/run/set/get/decrypt/keypair commands. Also trigger when the user wants to: commit .env files safely to git, stop sharing secrets over Slack/chat, encrypt environment variables with public-key cryptography, set up multi-environment .env configs (production/staging/ci), manage secrets in a monorepo with -fk flag, migrate from python-dotenv or plain dotenv to encrypted envs, inject env vars into any process across any language (Node, Python, Ruby, Go, Rust, etc.), or configure CI/CD pipelines (GitHub Actions, Docker) with encrypted env files. This skill contains the authoritative CLI reference — without it, responses will hallucinate non-existent commands and flags.
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.
Use this skill when designing OKR systems, writing performance reviews, running calibration sessions, creating PIPs, or building career ladders. Triggers on OKRs, performance reviews, calibration, PIPs, career ladders, leveling frameworks, feedback cycles, and any task requiring performance management system design.
Use this skill when configuring CRM workflows, managing sales pipelines, building forecasting models, or optimizing CRM data hygiene. Triggers on Salesforce, HubSpot, CRM workflows, pipeline management, deal stages, forecasting, CRM automation, and any task requiring CRM architecture or process optimization.
Use this skill when writing job descriptions, building sourcing strategies, designing screening processes, or creating interview frameworks. Triggers on job descriptions, candidate sourcing, screening criteria, interview loops, recruiting pipelines, offer management, and any task requiring talent acquisition process design.
Use this skill when building real-time data pipelines, stream processing jobs, or change data capture systems. Triggers on tasks involving Apache Kafka (producers, consumers, topics, partitions, consumer groups, Connect, Streams), Apache Flink (DataStream API, windowing, checkpointing, stateful processing), event sourcing implementations, CDC with Debezium, stream processing patterns (windowing, watermarks, exactly-once semantics), and any pipeline that processes unbounded data in motion rather than data at rest.
Use when editing, reviewing, or auditing DRF viewsets and serializers in PostHog. Triggers on files in posthog/api/, products/*/backend/api/, products/*/backend/presentation/, or any file importing rest_framework serializers or viewsets. Covers OpenAPI spec quality, field typing, schema annotations, and DRF best practices that flow through the type pipeline to generated TypeScript types and MCP tools.
Interactive skill for eliciting, formalizing, and persisting DynamoDB access patterns. Use when the user wants to start designing a DynamoDB table, define entities, or document how their application will read and write data. This is Step 1 of a 3-step pipeline: access patterns -> table design -> query interfaces. The output is a structured .md file that feeds into the dynamodb-table-design skill.
2-stage pipeline: trace (causal investigation) -> deep-interview (requirements crystallization) with 3-point injection
Multi-agent pipeline orchestrator that plans and dispatches parallel development tasks to worktree agents. Reads project context, configures task directories with PRDs and jsonl context files, and launches isolated coding agents. Use when multiple independent features need parallel development, orchestrating worktree agents, or managing multi-agent coding pipelines.