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Found 21 Skills
Agent skill for performance-benchmarker - invoke with $agent-performance-benchmarker
You are **Performance Benchmarker**, an expert performance testing and optimization specialist who measures, analyzes, and improves system performance across all applications and infrastructure. Yo...
Generate realistic KPI benchmarks for an influencer campaign before launch based on industry, platform, creator tier, and budget. This skill should be used when setting performance expectations for a creator campaign, estimating reach engagement and conversion benchmarks before launch, building KPI targets for an influencer program, forecasting campaign performance by creator tier and platform, setting EMV and ROAS targets for a campaign brief, defining what good looks like for an upcoming creator activation, calibrating expectations for a gifting or paid campaign across Instagram TikTok or YouTube, or creating a benchmark framework to measure campaign success against. For calculating ROI after a campaign ends, see campaign-roi-calculator. For calculating engagement rates from actual post data, see engagement-rate-calculator-benchmarker. For building a full KPI framework tied to business objectives, see campaign-goal-to-kpi-framework-builder.
Expert performance testing and optimization specialist focused on measuring, analyzing, and improving system performance across all applications and infrastructure
Performance benchmarking expertise for shell tools, covering benchmark design, statistical analysis (min/max/mean/median/stddev), performance targets (<100ms, >90% hit rate), workspace generation, and comprehensive reporting
Calculate influencer campaign ROI and build a leadership-ready narrative summary from raw performance data. This skill should be used when calculating ROI for a creator campaign, building a campaign performance report for leadership, turning raw influencer metrics into an executive summary, computing CPM CPE ROAS and EMV for a creator program, summarizing campaign spend versus revenue for a stakeholder meeting, proving influencer marketing ROI to a CMO or VP, creating a campaign wrap report with financial metrics, or comparing influencer channel efficiency against paid social. For setting KPI targets before a campaign launches, see performance-benchmark-setter. For tracking creator posting compliance, see creator-posting-compliance-tracker. For full end-of-campaign reporting with qualitative analysis, see post-campaign-creator-scorecard. For building UTM links to enable attribution, see utm-parameter-builder.
Build a complete KPI framework for a creator marketing campaign from a business objective. This skill should be used when setting KPIs for an influencer campaign, building a measurement plan before campaign launch, mapping business objectives to creator marketing metrics, defining primary and secondary KPIs for a creator program, creating a metrics framework for an awareness or conversion campaign, setting measurement benchmarks by creator tier, building a KPI dashboard structure for influencer reporting, or defining success criteria before activating creators. For calculating ROI after a campaign ends, see campaign-roi-calculator. For setting numeric benchmark targets, see performance-benchmark-setter. For tracking creator posting compliance, see creator-posting-compliance-tracker.
Use when migrating from SwiftData to SQLiteData — decision guide, pattern equivalents, code examples, CloudKit sharing (SwiftData can't), performance benchmarks, gradual migration strategy
Advanced test optimization with cargo-nextest, property testing, and performance benchmarking. Use when optimizing test execution speed, implementing property-based tests, or analyzing test performance.
Recommend and customize Megatron Bridge recipes for a user's model, GPU count, and training goal. Indexes library recipes (pretrain/SFT/PEFT) and performance recipes.
AscendC Operator End-to-End Development Orchestrator. Used when users need to develop new operators, implement custom operators, or complete the full process from requirements to testing. Keywords: operator development, end-to-end, full process, workflow orchestration, new operator creation.
Representative MoE training playbooks by hardware platform and model family. Summarizes rounded throughput bands, parallelism patterns, and common tuning stacks.