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Found 63 Skills
Performance optimization expert covering profiling, benchmarking, memory allocation, SIMD, cache optimization, false sharing, lock contention, and NUMA-aware programming.
Automates benchmark test creation for C++ projects using Google Benchmark with consistent software testing patterns. Use when creating performance benchmarks, profiling tests, or when the user mentions benchmarking, Google Benchmark, or performance testing.
Run Microsoft's eval-recipes benchmarks to validate amplihack improvements against baseline agents. Auto-activates when testing improvements, running evals, or benchmarking changes.
Spatial indexing and world streaming for Three.js building games with thousands of pieces. Use when optimizing building games, implementing spatial queries, chunk loading, or profiling performance. Includes spatial hash grids, octrees, chunk managers, and benchmarking tools.
Perform a deep competitive analysis for a solopreneur business. Use when mapping competitors in detail, finding exploitable gaps, understanding competitor strategy, benchmarking your own offering, or deciding how to position against the field. Goes deeper than the broad landscape mapping in market-research — this is focused dissection of specific competitors. Trigger on "analyze my competitors", "competitive analysis", "who are my competitors", "competitor deep-dive", "how do I beat the competition", "competitive landscape", "benchmark against competitors".
Senior SaaS CFO / Financial Analyst (15+ years) specialized in financial modeling, projections, and exit strategy for bootstrapped and VC-backed SaaS companies. Activate when user needs: (1) Revenue projections (1-5 years), (2) Exit valuation and multiples, (3) Unit economics analysis (CAC, LTV, payback), (4) Scenario modeling (conservative/base/optimistic), (5) Fundraising narratives with financial backing, (6) M&A due diligence financials, (7) SaaS metrics benchmarking, (8) Cohort analysis and churn modeling. Triggers: "proyecciones", "projections", "exit", "valuation", "ARR", "MRR", "multiples", "revenue forecast", "financial model", "exit strategy", "CAC", "LTV", "unit economics", "churn", "fundraising", "M&A", "acquisition", "5 year plan".
Track and analyze content performance across Instagram, YouTube, LinkedIn, Twitter/X, and Reddit using anysite MCP server. Measure engagement metrics, analyze post effectiveness, benchmark content strategy, identify top-performing content, and optimize posting strategies. Supports post performance tracking, engagement analysis, content type comparison, and competitive benchmarking. Use when users need to measure content ROI, optimize social strategy, identify viral content patterns, or analyze content engagement across platforms.
Optimizes Python library performance through profiling (cProfile, PyInstrument), memory analysis (memray, tracemalloc), benchmarking (pytest-benchmark), and optimization strategies. Use when analyzing performance bottlenecks, finding memory leaks, or setting up performance regression testing.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
Terminal-Bench integration for Mux agent benchmarking and failure analysis
CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试
Create an AI Evals Pack (eval PRD, test set, rubric, judge plan, results + iteration loop). Use for LLM evaluation, benchmarks, rubrics, error analysis/open coding, and ship/no-ship quality gates for AI features.