Testing & Quality skills

Browse reusable Agent Skills, each with a clear purpose and practical guidance.

doca-flow-tune

Use this skill when the user is tuning a live or captured `doca-flow` pipeline with `doca_flow_tune` — snapshotting pipe / counter / KPI state, picking a tuning axis (rule placement, resource hints / table sizing, HW-offload mode) and a matching measurement (rule-install rate, lookup latency, hardware-counter delta), running offline or online (read-only or state-changing) modes, reading the dumper CSV / analyze JSON / visualize mermaid, or applying a recommendation back into the Flow program. Trigger even when the user does not explicitly mention "doca_flow_tune" — typical implicit phrasings include "Flow rule-install rate is low on BlueField", "table sizing looks wrong for this pipe", "tune visualize step is empty", "before/after counters don't move", or "which doca-flow knob does this recommendation hit". Refuse and route elsewhere for measuring baseline numbers (doca-flow-perf, doca-flow-dpa-perf), writing the doca-flow application, DOCA install, or streaming Flow telemetry — those belong to other skills.

2.52k repo starsObserved in 2 repos
Testing & Quality
GitHub

doca-gpunetio-ib-write-bw

Use this skill when the user is building, running, or interpreting the doca/tools/gpunetio_ib_write_bw client+server benchmark — a CUDA kernel on the server posts RDMA WRITE work requests through the doca-gpunetio device-side surface to measure sustained GPU-driven WRITE bandwidth on a GPU+IB-device pair. Trigger even when the user does not explicitly mention "doca-gpunetio-ib-write-bw" or "GPUNetIO" — typical implicit phrasings include "measure WRITE BW when the GPU posts the WRs", "BW swings between runs on the same flags", "is the NIC saturated or am I CPU-bound on the CUDA kernel", "meson compile fails for the GPUNetIO bw tool", "nvidia_peermem isn't picking up my GPU buffer", or "GPU-initiated WRITE throughput vs CPU-initiated perftest". Refuse and route elsewhere for general doca-gpunetio library work, DOCA install, the GPU-initiated WRITE latency analog, the CPU-initiated upstream perftest, or application-level end-to-end throughput — those belong to other skills.

2.52k repo starsObserved in 2 repos
Testing & Quality
GitHub

doca-gpunetio-ib-write-lat

Use this skill when the user is measuring GPU-kernel-initiated RDMA WRITE latency through doca-gpunetio — building and running the `gpunetio_ib_write_lat` client + server pair under `doca/tools/gpunetio_ib_write_lat/`, checking GPU-NIC pairing, reading the half-iter / full-iter / CUDA-side usec columns, characterizing median / p99 / jitter for a real-time control loop, picking GPUNetIO vs GPI vs CPU-initiated `perftest`, or weighing the latency-vs-batching trade-off. Trigger even without 'GPUNetIO' or 'ib_write_lat': 'GPU kernel RDMA latency benchmark', 'how fast can a CUDA kernel post a WRITE', 'p99 RDMA latency on H100 + ConnectX', 'kernel-launched WR tail latency', or 'compare GPU-init vs CPU-init perftest'. Route elsewhere for bandwidth runs (doca-gpunetio-ib-write-bw), the GPI surface (doca-gpi), library debugging (doca-gpunetio), or DOCA install.

2.52k repo starsObserved in 2 repos
Testing & Quality
GitHub

doca-telemetry-utils

Use this skill when the user is invoking `doca_telemetry_utils` on a host with DOCA installed — discovering the diagnostic-counter schema, translating counter names to binary Data IDs, validating per-device counter support before committing a DOCA Telemetry exporter config, or reverse-resolving a captured Data ID. Trigger even when the user does not explicitly mention "doca_telemetry_utils" or "Data ID" — typical implicit phrasings include "my exporter ships but the collector sees nothing", "this metric silently drops downstream", "which counters does this BlueField expose", "translate this 0x... back to a counter name", "what do node / pcie_index / depth mean here", or "is this counter supported on this device before I commit it". Refuse and route elsewhere for developer-side collector / exporter library programming, DTS deployment, or DOCA install / repair — those belong to doca-telemetry, doca-public-knowledge-map, and doca-setup.

2.52k repo starsObserved in 2 repos
Testing & Quality
GitHub

unit-testing

为 BK-CI 代码编写单元测试时使用，例如 JUnit5、MockK、测试组织、依赖 Mock、异常校验和 TDD 场景。当用户要补测试或用测试驱动实现时优先使用。

2.51k repo starsObserved in 1 repos
Testing & Quality
GitHub

consult-codex

Dual-AI code analysis pairing OpenAI Codex GPT-5.6-terra with Claude code-searcher — the lightest consult variant, two citation-verified perspectives. Use for a quick second opinion on a code question.

2.51k repo starsObserved in 2 repos
Testing & Quality
GitHub

consult-zai

Dual-AI code analysis pairing z.ai GLM 5.2 with Claude code-searcher — a lightweight two-model second opinion. Use for a quick z.ai-backed check on a code question.

2.51k repo starsObserved in 1 repos
Testing & Quality
GitHub

benchmark-tune

Use this skill when running, debugging, interpreting, or documenting mesh-llm benchmark tune model-serving throughput trials, including choosing ctx/batch/ubatch/mmap/mlock/speculative-decoding sweeps, running benchmark tune on local or SSH hosts, collecting JSON evidence, and applying tolerance-aware recommendations. Trigger for requests mentioning benchmark tune, tuning tok/s, ctx_size tradeoffs, mmap or mlock tuning, speculative decoding, MTP, ngram, draft models, or replacing old gpu tune usage.

2.50k repo starsObserved in 1 repos
Testing & Quality
GitHub

kv-tool-loop-stability

Use this skill when certifying mesh-llm KV/cache stability under repeated OpenAI tool-call loops, same-prefix cache reuse, suffix-prefill limits, or native Skippy slot/decode/eviction failures.

2.50k repo starsObserved in 1 repos
Testing & Quality
GitHub

skippy-cache-family-bench

Use this skill when benchmarking Skippy exact-prefix cache across model families, comparing Skippy against llama-server, producing README benchmark tables, updating crates/skippy-cache/README.md evidence, or diagnosing cache benchmark gaps by family or Hugging Face use case.

2.50k repo starsObserved in 1 repos
Testing & Quality
GitHub