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Found 7,881 Skills
Generate and validate Apex test classes with TestDataFactory patterns, bulk testing (251+ records), mocking strategies, assertion best practices, and disciplined test-fix loops. Use this skill when creating new Apex test classes, improving test coverage, debugging and fixing failing Apex tests, running test execution and coverage analysis, or implementing testing patterns for triggers, services, controllers, batch jobs, queueables, and integrations. Triggers on *Test.cls, *_Test.cls files, sf apex run test workflows, coverage reports, test-fix loops. Do NOT trigger for production Apex code (use generating-apex) or Jest/LWC tests.
Provides a structured workflow for migrating an Android XML View to Jetpack Compose. This skill details the step-by-step process, from planning and dependency setup, to theming and layout migration, validation and XML cleanup. Use this skill when you need to migrate an XML View to Jetpack Compose in an Android project. It solves the problem of converting the UI of a legacy XML View into modern, declarative Compose components while maintaining interoperability.
Analyze official Megatron-LM commits, PRs, and branch change sets to identify feature evolution, candidate breaking changes, and migration-relevant events. Use when Codex already has a normalized Megatron change set and needs to explain what changed, which new features matter, and which changes should flow into MindSpeed adaptation work.
HCCL (Huawei Collective Communication Library) performance testing for Ascend NPU clusters. Use for testing distributed communication bandwidth, verifying HCCL functionality, and benchmarking collective operations like AllReduce, AllGather. Covers MPI installation, multi-node pre-flight checks (SSH/CANN version/NPU health), and production testing workflows.
Optimize the performance of Triton operators optimized for Ascend NPU. This guide is for users who need to optimize the performance of Triton operators on Ascend NPU, resolve UB overflow, improve Cube unit utilization, and design Tiling strategies.
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.
Ascend C Code Inspection Skill. Conduct security specification inspection on code based on the hypothesis testing methodology. When calling, you must clearly provide: code snippets and inspection rule descriptions. TRIGGER when: Users request code inspection, code review, ask code security questions, check coding specifications, or need to check specific code issues (such as memory leaks, integer overflows, null pointers, etc.). Keywords: Ascend C, code inspection, code review, security specification, memory, pointer, overflow, leak, coding specification.
Task Orchestration for Full-Process Development of Ascend Triton Operators. Used when users need to develop Triton Operators, covering the complete workflow of environment configuration → requirement design → code generation → static inspection → precision verification → performance evaluation → document generation → performance optimization.
Use when app feels slow, memory grows, battery drains, or diagnosing ANY performance issue. Covers memory leaks, profiling, Instruments workflows, retain cycles, performance optimization.
Guides use of ProjectDiscovery Katana for web crawling and spidering in security testing and recon workflows. Covers installation, standard vs headless mode, scope and rate limits, JSONL output, and piping from httpx or URL lists. Use when the user mentions Katana, projectdiscovery/katana, web crawling, spidering, endpoint discovery, attack surface mapping, or chaining crawlers in automation pipelines.
Step-by-step wallet investigation workflow using Range AI MCP tools (risk score, sanctions, connections, transfers, funded-by, entities, cross-chain pivots) plus a one-shot prompt template. Use when the user runs investigations inside an MCP-connected client with Range enabled, or needs a structured checklist alongside crypto-investigation-compliance—not as legal advice or a substitute for Range’s live docs and API scopes.
Investigates hypotheses that MEV activity (bundles, searchers, same-block ordering) temporally overlaps or co-occurs with launch-phase rug signals—using public txs, bundle IDs, and clustering with explicit confidence. Use when the user asks about MEV plus rug coordination, launch sniper bundles, Jito or Flashbots overlap with dev exits, or joint profit-flow case studies—not for alleging collusion without evidence, harassing addresses, or live interference.