'benchmark' 검색 결과

Carry out Benchmark Email tasks through Rube MCP, which links an AI agent with external tools. The skill discovers supported actions and their input formats, confirms an active connection, and executes the requested operations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding supported Benchmark Email actions
• Checking the connection before running a task
• Batching multiple Benchmark Email operations

Carry out Benchmark Email tasks through Rube MCP, which links an AI agent with external tools. The skill discovers supported actions and their input formats, confirms an active connection, and executes the requested operations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding supported Benchmark Email actions
• Checking the connection before running a task
• Batching multiple Benchmark Email operations

Set up and run kube-bench to check Kubernetes configuration against CIS security benchmarks. Select the appropriate benchmark and cluster components, then export JSON or JUnit results for automated pipelines and troubleshoot skipped checks or incorrect detection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up kube-bench for the first time
• Selecting benchmark versions and scan targets
• Exporting JSON or JUnit results for CI

Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Phase 2B of the Gaia evidence verification pipeline. Verifies benchmark-result rows and benchmark-source candidates against registry/benchmark-sources.json before adversarial audit, link validation, catalog promotion, or ingestion. Use when running /ev-pipeline, checking benchmark-result evidence, reviewing benchmark-source candidates, or preparing benchmark rows for /gaia-ingest-batch.

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Local-only regression / benchmark skill for ui-clone-skills maintainers. Drives the standard ui-reverse-engineering pipeline against the canonical reference site (https://realfood.gov) and records AE/SSIM, iteration count, gate fail counts, and outcome to benchmark/history.csv so prompt / sub-doc / model-version drift surfaces as a trend. Trigger phrases: "run benchmark" / "regression benchmark" / "benchmark clone". The Makefile no longer has a `benchmark` target — setup is inline bash in this skill (Step 1 below). Internal: NOT registered in `.claude-plugin/plugin.json` `skills`. Not part of the public 3-skill marketplace surface. Maintainer tooling only.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Display a text scoreboard of published Ponytail 5 benchmark results, comparing code volume, generated text tokens, cost, time, and check results against an agent without the skill. The figures describe benchmark averages, not savings in the current project.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• View published code volume and cost comparisons
• Review benchmark correctness and testing figures
• Check benchmark conditions alongside the results

Audit AWS, Azure, and GCP configurations against CIS Benchmarks, security configuration guidelines. Use automated scan results to identify failed checks, prioritize fixes, report compliance by area, and establish ongoing monitoring for configuration changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Running an initial cloud security configuration audit
• Preparing CIS-related evidence for SOC 2 or ISO 27001 audits
• Prioritizing fixes for failed security checks

Evaluate language models on knowledge, math, coding, safety, and image understanding benchmarks. The skill guides reproducible runs in containers using local Docker, Slurm clusters, or cloud execution, with shared configurations for model comparison and result export.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing models on the same benchmark tasks
• Running a small evaluation sample before a full benchmark
• Running large evaluations on a Slurm cluster

Design or extend DataFusion benchmarks using SQL where practical. Select representative workload variations, keep unrelated processing lightweight, and integrate runs with bench.sh so measurements reflect useful execution paths and remain practical to run.

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• Add SQL benchmarks for DataFusion operators
• Select representative input sizes and filter conditions
• Reduce unrelated processing overhead in measurements

회사의 서비스, 고객상, 차별화 근거를 바탕으로 비교할 경쟁사와 조사 출처를 고릅니다. 직접·인접 경쟁사와 목표 기업으로 분류하고 출처가 있는 후보 목록을 만듭니다.

• 자세히 비교할 경쟁사 선정
• 직접·인접 경쟁사와 목표 기업 분류
• 시장 조사 보고서의 후보 압축

웹 페이지 표시와 조작, API 응답, 빌드와 테스트의 소요 시간을 측정합니다. 변경 전후 결과를 비교하고 Git으로 공유하는 기준값을 바탕으로 성능 저하를 확인합니다.

• 코드 변경 전후 성능을 비교합니다
• 페이지가 느리다는 보고를 조사합니다
• 출시 전 성능 목표를 확인합니다

View published benchmark results comparing ponytail with the same agent without the skill. A simple bar chart shows code volume, output tokens, cost, time, and quality checks, clearly separated from results for the current project.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check benchmark results for code and cost savings
• Compare execution time and output tokens
• Review quality checks alongside savings

Benchmark distributed consensus protocols, methods computers use to agree on shared results. Compare processing rates, response times, scaling behavior, and resource usage across Byzantine, Raft, and Gossip, then identify bottlenecks and potential tuning changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing Byzantine, Raft, and Gossip performance
• Measuring response times under increasing load
• Finding CPU, memory, or network bottlenecks

Assess language models with over 60 academic benchmark tests using consistent prompts and scoring. Compare models, track performance during training, and organize research results with support for HuggingFace models, vLLM, and APIs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare models on standard knowledge and reasoning tests
• Track model performance across training checkpoints
• Organize evaluation results for research reports

Evaluate language models with over 100 benchmark tests covering knowledge, math, coding, safety, and image understanding. Configure runs on Docker, Slurm computing clusters, or cloud infrastructure, compare models, and export results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare models using the same benchmark tests
• Run large evaluations on a Slurm cluster
• Evaluate safety and image understanding

Evaluate code generation models with HumanEval, MBPP, and other benchmarks. Test generated programs, compare models across programming languages, and record pass@k scores, which estimate the chance that at least one of k solutions passes the tests.

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• Comparing code generation models on shared benchmarks
• Measuring correctness across programming languages
• Evaluating models trained to follow instructions

Run MNN checks and regression tests on a host computer or Android device, with stage summaries and failure logs. A separate workflow benchmarks LLM prompt processing and token generation on real iPhones and iPads, including branch comparisons.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Run static checks and host regression tests
• Verify selected backends on an Android device
• Benchmark LLM speed and compare branches on iPhone or iPad

Assess language models with over 60 academic benchmark tests using consistent prompts and scoring. Compare models, track performance during training, and organize research results with support for HuggingFace models, vLLM, and APIs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare models on standard knowledge and reasoning tests
• Track model performance across training checkpoints
• Organize evaluation results for research reports

Evaluate code generation models with HumanEval, MBPP, and multilingual benchmarks. The skill guides test execution and model comparisons using pass@k, an estimate of whether at least one of k generated solutions passes the tests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare code generation models on shared benchmarks
• Measure code generation performance across languages
• Evaluate instruction-tuned coding models

Operate or analyze LoopX-managed benchmark experiments through benchmark-toolkit, including trajectory-based effectiveness and efficiency diagnosis, matched comparisons, run selection and integrity. Solving an assigned task under an existing runner does not by itself select this skill. Excludes casual benchmark discussion and ordinary software microbenchmarks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dontbesilent 对标分析。用五重过滤法帮你找到值得模仿的对标，排除一切关于「我」的噪音。 触发方式：/dbs-benchmark、/对标、「帮我找对标」「我该模仿谁」 Benchmark analysis using dontbesilent's five-filter method. Trigger: /dbs-benchmark, "find me a benchmark", "who should I copy"

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