Results for “benchmarking”

Nexscope Ozon Russia seller drill-down product list by seller ID. Returns all SKUs under a seller with complete metrics: sales, revenue, price, rating, stock, turnover, lost revenue, supporting multi-dimensional numeric filters, sorting, and currency conversion. Use for store structure analysis, seller bestseller analysis, competitor store benchmarking. Trigger when the user mentions Ozon seller products, Ozon store analysis, Ozon seller drill-down, Ozon seller SKUs, Ozon store bestsellers, Ozon competitor store, Nexscope seller, Ozon seller drill-down, Ozon shop audit, Russian marketplace seller SKUs, Ozon store structure. Also trigger when the intent is to view all products and their sales performance under an Ozon seller ID, even without explicitly mentioning Nexscope.

The English summary is being prepared. Showing the original description.

Use Nexscope data to find and analyze competitors on Amazon, covering 12 marketplaces, with product metrics including sales, BSR, pricing, ratings, and growth trends. Trigger when the user mentions competitor lookup, competitor analysis, ASIN reverse lookup, competitive product research, finding similar products, market competitor discovery, product benchmarking, competitor sales estimation, analyzing competitor listings, competitor analysis, ASIN reverse lookup, competitor sales, competitor research, Nexscope, market competitor discovery, competitor trends. Even if the user does not explicitly mention "Nexscope" or "competitor lookup", if their need involves discovering and analyzing Amazon competitors by ASIN, keyword, seller name, brand, or category, this skill should also be triggered.

The English summary is being prepared. Showing the original description.

Financial services advisory skill for consulting engagements. Use when preparing research briefs on banking, insurance, capital markets, or wealth management, building performance benchmarking frameworks, regulatory impact assessments, or stakeholder materials for CFOs, CROs, and technology leaders.

The English summary is being prepared. Showing the original description.

Design compensation framework - salary bands, equity philosophy, offer templates, and total comp benchmarking. Use when asked to "design our comp bands", "how much equity should we give", "is our comp competitive", or "write an offer template".

The English summary is being prepared. Showing the original description.

用户要找对标账号/分析竞品爆款/找差异化选题时;或问"怎么做AI工具赛道的差异化""how to find benchmarks / differentiate"时。按5步走:找3-5个低粉高爆对标(搜索from:xxx min_faves:10)→分析90天爆款抓隐性需求→学互动策略→拆变现模式→三公式变形(场景细化/人群聚焦/观点反转)出差异。不适用于:已有定位日常发内容(→x-short-content-craft)、纠结选IP还是泛流量(→x-positioning-tradeoff)、检查草稿(→x-five-piece-checklist)、纯信息查询。

The English summary is being prepared. Showing the original description.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

The English summary is being prepared. Showing the original description.

Expert competitive analyst specializing in competitor intelligence, strategic analysis, and market positioning. Masters competitive benchmarking, SWOT analysis, and strategic recommendations with focus on creating sustainable competitive advantages.

The English summary is being prepared. Showing the original description.

Expert FinOps guidance for cloud, AI, and SaaS technology spend. Covers AI cost management, agentic FinOps, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, open-weight vendor APIs (DeepSeek, Qwen, Kimi, GLM), AWS (EC2, Bedrock, SageMaker, Savings Plans, CUR), Azure (reservations, AHB, OpenAI PTUs), GCP (Vertex AI, BigQuery), OCI, on-prem and hybrid, Kubernetes cost allocation, data platforms (Databricks, Fabric F-SKUs, Snowflake), tagging governance, SaaS management (SAM, shadow IT), AI coding tools (Cursor, Claude Code, Copilot, Codex), ITAM, allocation, showback, chargeback, anomaly management, KPIs and benchmarking, forecasting, waste detection playbooks, workload onboarding and M&A, and GreenOps (cloud carbon, CSRD). Use for any technology cost or waste question in your estate - expiring commitments or RIs, NAT gateway bills, idle VMs, snapshot sprawl - and for commitment sizing, rightsizing, or connecting spend to business value. Built by OptimNow.

The English summary is being prepared. Showing the original description.

Nature-style engineering manuscript reviewer skill for testing devices, robots, platforms, systems, algorithms embodied in physical systems and engineering methods against requirements, validation, benchmarking, uncertainty, robustness and failure modes.

The English summary is being prepared. Showing the original description.

Rates any SKILL.md on a 0-100 scale across 10 dimensions with a SHIP / REWORK / SCRAP verdict. Evaluates trigger precision, instruction clarity, output predictability, edge case coverage, anti-hallucination guardrails, developer experience, composability, open-source readiness, wow factor, and real-world utility. No flattery — calibrated against Anthropic's own skill-creator rubric. Use this skill whenever someone says "score this skill", "rate my skill", "is this skill good", "skill review", "skill audit", "roast my SKILL.md", "grade this", "will this skill work", "evaluate my skill", "how good is this", or pastes a SKILL.md and asks for feedback. Also trigger when comparing two skills, benchmarking a skill collection, or asking "what's wrong with this skill" — even without the word "score".

The English summary is being prepared. Showing the original description.

Use when building imp, running its test suite, checking CI status, or debugging build/test failures - "make build", "run the tests", "test-gpu", "verify-fast", GTEST_FILTER, Docker/CUDA toolchain, dependency bumps, "CI is red/blocked", "which gate failed", stale objects / segfault after a header edit, hook edits, docker-entrypoint env vars, determinism or perplexity checks. Do NOT use for benchmarking/profiling (benchmark-cuda) or output-quality batteries (check-degeneration).

The English summary is being prepared. Showing the original description.

Use when benchmarking, profiling, or A/B-testing CUDA kernels or end-to-end perf in the imp inference engine on RTX 5090 (sm_120), including refreshing tests/perf_baseline.json or publishing numbers to docs/BENCHMARKS.md and the README. Triggers on "benchmark kernel", "profile cuda", "ncu", "nsys", "kernel timing", "kernel sum", "occupancy", "bandwidth bound", "compute bound", "roofline", "perf baseline", "is this regression real", "decode dropped", "aggregate throughput", "two-image A/B", "prefill kernel A/B". Do NOT use for writing/optimizing kernel code (sm120-cuda-expert) or output-quality checks (check-degeneration).

The English summary is being prepared. Showing the original description.

Monitors secondary market pricing trends with discount/premium analysis, bid-ask spreads, and market-clearing dynamics. Use when analyzing secondary pricing, tracking market trends, or benchmarking transaction levels.

The English summary is being prepared. Showing the original description.

Constructs fund-level performance reporting with IRR, MOIC, DPI, RVPI, PME, and vintage year benchmarking. Use when building fund reports, calculating performance metrics, or preparing LP reporting packages.

The English summary is being prepared. Showing the original description.

Computes fund performance with gross/net IRR, MOIC, DPI, RVPI, TVPI, PME, and direct alpha methodologies. Use when calculating fund performance, reconciling return metrics, or benchmarking against peer groups.

The English summary is being prepared. Showing the original description.

Deconstructs SaaS operating metrics including ARR, NRR, gross retention, magic number, rule of 40, and cohort economics. Use when analyzing SaaS businesses, benchmarking software metrics, or evaluating subscription model health.

The English summary is being prepared. Showing the original description.

Evaluates transportation assets with ridership analysis, fare structure assessment, and operating efficiency benchmarking. Use when analyzing transportation projects, evaluating mass transit, or assessing toll road economics.

The English summary is being prepared. Showing the original description.

Evaluates structured product tranche pricing with spread analysis, yield attribution, and comparable structure benchmarking. Use when assessing tranche value, comparing structured product pricing, or analyzing spread components.

The English summary is being prepared. Showing the original description.

Values infrastructure assets with DCF, regulated asset base, and comparable transaction methodologies adjusted for regulatory and contractual frameworks. Use when valuing infrastructure assets, analyzing regulated utilities, or benchmarking infra transactions.

The English summary is being prepared. Showing the original description.

Evaluates credit fund returns with yield attribution, mark-to-market dynamics, and performance comparison across credit strategies. Use when analyzing credit fund performance, decomposing returns, or benchmarking credit strategies.

The English summary is being prepared. Showing the original description.

Deploy machine learning models to edge devices using Google AI Edge Gallery, TensorFlow Lite, ONNX Runtime, and MediaPipe. Covers model quantization (INT8/INT4), on-device inference with Gemma 4 models, Android/iOS deployment via AI Edge Gallery, hardware delegate selection (GPU/NPU/DSP), and performance benchmarking on constrained devices. Use when deploying models to mobile phones, IoT devices, or embedded systems where cloud inference is impractical due to latency, cost, or connectivity constraints.

The English summary is being prepared. Showing the original description.

Competitive reputation benchmarking against direct competitors

The English summary is being prepared. Showing the original description.

Use when implementing pool/slab/arena allocators, tuning jemalloc/mimalloc/tcmalloc, writing a Rust GlobalAlloc, or benchmarking allocator performance and fragmentation.

The English summary is being prepared. Showing the original description.

Use when writing, optimizing, or benchmarking a C++ CPU kernel with AVX2 or AVX512 intrinsics for the Hugging Face kernels ecosystem. Not for CUDA kernels: use cuda.

The English summary is being prepared. Showing the original description.