Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Best practices for creating ISPC lit tests. Use when writing regression tests, verifying code generation, or checking compiler diagnostics.
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A concise guide for writing lit tests for the ISPC. These tests ensure compiler correctness, verify generated code, and prevent regressions.
Use lit tests when validating:
--nowrapPrevents line wrapping in compiler output for consistent FileCheck matching:
// RUN: %{ispc} %s --target=host --nowrap --emit-llvm-text -o - | FileCheck %s
--nostdlib When Not Testing Library CodeSimplifies test output and avoids unrelated symbols:
// RUN: %{ispc} %s --target=host --nostdlib --nowrap -o - | FileCheck %s
export Unless Testing Itexport functions generate both masked and unmasked IR — doubling the verification effort.
// Preferred
void foo() { ... }
// Avoid unless explicitly testing export behavior
export void foo() { ... }
Use --target=host unless verifying target-specific codegen:
// RUN: %{ispc} %s --target=host --nowrap -o - | FileCheck %s
Avoid hardcoding vector widths or variable names.
Use named patterns like [[WIDTH]] and [[TYPE]].
Example:
// CHECK-NEXT: %test = sdiv <[[WIDTH:.*]] x i32> %a, %b
// CHECK-NEXT: ret <[[WIDTH]] x i32> %test
When order is flexible:
// CHECK-DAG: {{%.*}} = shufflevector <[[WIDTH:.*]] x [[BASE_TYPE:i.*]]> {{%.*}}, <[[WIDTH]] x [[BASE_TYPE]]> {{poison|undef}}, <[[WIDTH]] x [[BASE_TYPE]]> zeroinitializer
Tip: Avoid relying on exact variable names — they differ between OS and LLVM versions.
When output differs by architecture or ISA:
REQUIRES: directive for conditional execution.Example:
// RUN: %{ispc} %s --target=avx512skx-x16 --emit-asm -o - | FileCheck %s
// REQUIRES: X86_ENABLED
REQUIRES for Feature DependenciesDefined in tests/lit-tests/lit.cfg:
X86_ENABLED, LLVM_*_0+, etc.%{ispc}, %s, %tUse --debug-phase to capture output of specific optimization passes:
// RUN: %{ispc} %s --target=avx2 --emit-llvm-text \
// RUN: --debug-phase=325:325 --dump-file=%t -o /dev/null
// RUN: FileCheck --input-file %t/ir_325_LoadStoreVectorizerPass.ll %s
Clearly describe what the test verifies and why it exists.
Example:
// Verifies that stmxcsr/ldmxcsr intrinsics correctly set/restore FTZ/DAZ flags
// when --opt=reset-ftz-daz is enabled.
// Brief description of the test purpose
// RUN: %{ispc} %s --target=host --nostdlib --nowrap --emit-llvm-text -o - | FileCheck %s
// REQUIRES: <feature_if_needed>
// CHECK-LABEL: @function_name___
// CHECK: expected pattern
// CHECK-NOT: unexpected pattern
void function_name() {
// Minimal reproducible test code here
}
Run all lit tests:
cmake --build build --target check-all -j $(nproc)
To test the specific test, run:
TEST=/full/path/test.ispc cmake --build build --target check-one -j $(nproc)
####.ispc, where #### is the GitHub issue number.feature-name-1.ispc, feature-name-2.ispc).아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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