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Found 4,069 Skills
Use when determining optimal posting times on Xiaohongshu, scheduling content for maximum engagement, analyzing audience activity patterns, or testing different publish times to improve content performance
Plan resource capacity — workload analysis and utilization forecasting. Use when heading into quarterly planning, the team feels overallocated and you need the numbers, deciding whether to hire or deprioritize, or stress-testing whether upcoming projects fit the people you have.
This skill should be used when the user asks to "write pytest tests", "set up pytest best practices", "configure pytest", "write fixtures", or needs guidance on pytest testing patterns and project structure.
This skill should be used when the user asks to "create a GitHub Actions workflow", "set up CI/CD", "configure GitHub Actions", "add automated testing", "deploy with GitHub Actions", or needs guidance on GitHub Actions workflows, syntax, or automation.
Multi-agent management workflow — task delegation, progress monitoring, quality verification with regression testing, feedback delivery, and cross-review orchestration. Use this skill when coordinating multiple agents on a shared task, monitoring delegated work, ensuring quality across agent outputs, or implementing a multi-phase plan (3+ phases or 10+ file changes).
Use this skill when applying Jobs-to-be-Done, building opportunity solution trees, mapping assumptions, or validating product ideas. Triggers on product discovery, JTBD, jobs-to-be-done, opportunity solution trees, assumption mapping, experiment design, prototype testing, and any task requiring product discovery methodology.
Expert guidance on building, debugging, and testing multiplatform iOS/Android apps and frameworks with Skip (skip.dev). Use when developers mention: (1) Skip, Skip.dev, skip-tools, or SkipStack, (2) building a multiplatform iOS+Android app from Swift/SwiftUI, (3) Skip Fuse (native) or Skip Lite (transpiled) modes, (4) transpiling Swift to Kotlin, (5) SwiftUI to Jetpack Compose bridging, (6) skip.yml configuration, (7) debugging Android builds from Xcode, (8) Skip CLI commands (skip create/init/test/export), (9) conditional compilation with #if SKIP or #if os(Android), (10) Skip Comments (SKIP INSERT/REPLACE/DECLARE/NOWARN), (11) bridging Swift and Kotlin code, (12) Skip module dependencies or Android Gradle configuration.
Execute a single task from a Jira task plan using a structured pipeline of specialist subagents: planning, testing, refactoring, implementation, documentation, code-quality review, architecture review, security audit, and requirements verification. The user must specify which task number to execute. Use when the user says "execute task 3", "work on task 2", "implement task 1", "start task 5 for PROJECT-1234", or "run task N". Also triggered by the orchestrating-jira-workflow skill as Phase 5 of the end-to-end pipeline (called once per task). Requires that the task plan exists at docs/<TICKET_KEY>-tasks.md. Executes ONLY the specified task — never continues to the next one without explicit user approval.
Use when the user needs prompt design, optimization, few-shot examples, chain-of-thought patterns, structured output, evaluation metrics, or prompt versioning. Triggers: new prompt creation, prompt optimization, few-shot example design, structured output specification, A/B testing prompts, evaluation framework setup.
Create and sign JSON Web Tokens (JWTs) for testing and development. Use when the user wants to generate, create, build, or sign a JWT — e.g. "create a JWT", "generate a test token", "sign this payload", "make a JWT with these claims", "build an access token". Supports HMAC, RSA, and ECDSA algorithms.
Use when you have a rough product idea and want a complete PRD without sitting through an interactive grilling. Claude walks the full decision tree (edge cases, modules, schema, testing, security), self-answers with software-engineering best practices, streams the Q&A live so you can override, and writes the PRD locally with an option to push as a GitHub issue.
Complete toolkit for Huawei Ascend NPU model conversion and end-to-end inference adaptation. Workflow 1 auto-discovers input shapes and parameters from user source code. Workflow 2 exports PyTorch models to ONNX. Workflow 3 converts ONNX to .om via ATC with multi-CANN version support. Workflow 4 adapts the user's full inference pipeline (preprocessing + model + postprocessing) to run end-to-end on NPU. Workflow 5 verifies precision between ONNX and OM outputs. Workflow 6 generates a reproducible README. Supports any standard PyTorch/ONNX model. Use when converting, testing, or deploying models on Ascend AI processors.