vercel-cost-tuning

webflow-cost-tuning

webflow-performance-tuning

windsurf-cost-tuning

windsurf-load-scale

windsurf-performance-tuning

windsurf-rate-limits

windsurf-reference-architecture

wispr-performance-tuning

workhuman-performance-tuning

npm-scripts-optimizer

security-benchmark-runner

performance-lighthouse-runner

tailwind-class-optimizer

gpu-resource-optimizer

inference-latency-profiler

compression-optimizer

spark-sql-optimizer

sql-query-optimizer

memorystore-config

Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.

Track session costs, set budget alerts, and optimize token spend. Use to check costs mid-session or set spending limits.

Show session analytics, learning patterns, correction trends, heatmaps, and productivity metrics. Computes stats from project memory and session history. Use when asking for stats, statistics, progress, how am I doing, coding history, or dashboard.

Like muscle memory for your coding sessions. Find and surface relevant learnings before you start working.

Reduce token waste by 40-60% through anti-sycophancy rules, tool-call budgets, one-pass coding, task profiles, and read-before-write enforcement. Inspired by drona23/claude-token-efficient.

Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class.

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Comprehensive PostGIS spatial table design reference covering geometry types, coordinate systems, spatial indexing, and performance patterns for location-based applications

Provides malware analysis and network traffic techniques for CTF challenges. Use when analyzing obfuscated scripts, malicious packages, custom crypto protocols, C2 traffic, PE/.NET binaries, RC4/AES encrypted communications, YARA rules, shellcode analysis, memory forensics for malware (Volatility malfind, process injection detection), anti-analysis techniques (VM/sandbox detection, timing evasion, API hashing, process injection, environment checks), or extracting malware configurations and indicators of compromise.

Architect (Aria). Use for system architecture (fullstack, backend, frontend, infrastructure), technology stack selection (technical evaluation), API design (REST/GraphQL/tRPC/We...

DeepAgent-style memory folding for VCO sessions: compress long context into structured working/tool memory without using episodic-memory.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

Codex compatibility layer for SuperClaude /sc:* commands with vibe-adapted routing.

Use when running performance benchmarks, establishing baselines, or validating regressions with sequential runs. Enforces 60s minimum runs (30s only for binary search) and no parallel benchmarks.

Use when mapping code paths, entrypoints, and likely hot files before profiling.

Optimize Entity Framework Core queries by fixing N+1 problems, choosing correct tracking modes, using compiled queries, and avoiding common performance traps. Use when EF Core queries are slow, generating excessive SQL, or causing high database load.

Guide developers through capturing diagnostic artifacts to diagnose production .NET performance issues. Use when the user needs help choosing diagnostic tools, collecting performance data, or understanding tool trade-offs across different environments (Windows/Linux, .NET Framework/modern .NET, container/non-container).

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Optimizes hot-path scalar loops in .NET 8+ with cross-platform Vector128/Vector256/Vector512 SIMD intrinsics, or replaces manual math loops with single TensorPrimitives API calls. Covers byte-range validation, character counting, bulk bitwise ops, cross-type conversion, fused multi-array computations, and float/double math operations.

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Analyze MSBuild binary logs to diagnose build failures by replaying binlogs to searchable text logs. Only activate in MSBuild/.NET build context. USE FOR: build errors that are unclear from console output, diagnosing cascading failures across multi-project builds, tracing MSBuild target execution order, investigating common errors like CS0246 (type not found), MSB4019 (imported project not found), NU1605 (package downgrade), MSB3277 (version conflicts), and ResolveProjectReferences failures. Requires an existing .binlog file. DO NOT USE FOR: generating binlogs (use binlog-generation), build performance analysis (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: dotnet msbuild binlog replay, grep, cat, head, tail for log analysis.

Guide for optimizing MSBuild build parallelism and multi-project scheduling. Only activate in MSBuild/.NET build context. USE FOR: builds not utilizing all CPU cores, speeding up multi-project solutions, evaluating graph build mode (/graph), build time not improving with -m flag, understanding project dependency topology. Note: /maxcpucount default is 1 (sequential) — always use -m for parallel builds. Covers /maxcpucount, graph build for better scheduling and isolation, BuildInParallel on MSBuild task, reducing unnecessary ProjectReferences, solution filters (.slnf) for building subsets. DO NOT USE FOR: single-project builds, incremental build issues (use incremental-build), compilation slowness within a project (use build-perf-diagnostics), non-MSBuild build systems. INVOKES: dotnet build -m, dotnet build /graph, binlog analysis.

Establish build performance baselines and apply systematic optimization techniques. Only activate in MSBuild/.NET build context. USE FOR: diagnosing slow builds, establishing before/after measurements (cold, warm, no-op scenarios), applying optimization strategies like MSBuild Server, static graph builds, artifacts output, and dependency graph trimming. Start here before diving into build-perf-diagnostics, incremental-build, or build-parallelism. DO NOT USE FOR: non-MSBuild build systems, detailed bottleneck analysis (use build-perf-diagnostics after baselining).

Guide for diagnosing and improving MSBuild project evaluation performance. Only activate in MSBuild/.NET build context. USE FOR: builds slow before any compilation starts, high evaluation time in binlog analysis, expensive glob patterns walking large directories (node_modules, .git, bin/obj), deep import chains (>20 levels), preprocessed output >10K lines indicating heavy evaluation, property functions with file I/O ($([System.IO.File]::ReadAllText(...))), multiple evaluations per project. Covers the 5 MSBuild evaluation phases, glob optimization via DefaultItemExcludes, import chain analysis with /pp preprocessing. DO NOT USE FOR: compilation-time slowness (use build-perf-diagnostics), incremental build issues (use incremental-build), non-MSBuild build systems. INVOKES: dotnet msbuild -pp:full.xml for preprocessing, /clp:PerformanceSummary.

Guide for optimizing MSBuild incremental builds. Only activate in MSBuild/.NET build context. USE FOR: builds slower than expected on subsequent runs, 'nothing changed but it rebuilds anyway', diagnosing why targets re-execute unnecessarily, fixing broken no-op builds. Covers 8 common causes: missing Inputs/Outputs on custom targets, volatile properties in output paths (timestamps/GUIDs), file writes outside tracked Outputs, missing FileWrites registration, glob changes, Visual Studio Fast Up-to-Date Check (FUTDC) issues. Key diagnostic: look for 'Building target completely' vs 'Skipping target' in binlog. DO NOT USE FOR: first-time build slowness (use build-perf-baseline), parallelism issues (use build-parallelism), evaluation-phase slowness (use eval-performance), non-MSBuild build systems. INVOKES: dotnet build /bl, binlog replay with diagnostic verbosity.

Guide for interpreting ResolveProjectReferences time in MSBuild performance summaries. Only activate in MSBuild/.NET build context. Activate when ResolveProjectReferences appears as the most expensive target and developers are trying to optimize it directly. Explains that the reported time includes wait time for dependent project builds and is misleading. Guides users to focus on task self-time instead. Do not activate for general build performance -- use build-perf-diagnostics instead.

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Golang data structures — slices (internals, capacity growth, preallocation, slices package), maps (internals, hash buckets, maps package), arrays, container/list/heap/ring, strings.Builder vs bytes.Buffer, generic collections, pointers (unsafe.Pointer, weak.Pointer), and copy semantics. Use when choosing or optimizing Go data structures, implementing generic containers, using container/ packages, unsafe or weak pointers, or questioning slice/map internals.