MCP App StoreMCP App StoreSKILL.md packages that extend Claude Code, Cursor, Copilot, and other AI agents.
Tags
arize-skills
Create, run, and analyze Arize experiments for evaluating and comparing model performance using the ax CLI.
kernels
Guidance and examples for writing, benchmarking, and integrating optimized Triton kernels on ROCm (MI355X, R9700) for diffusers and transformers workloads.
awesome-copilot
Create, run, and analyze Arize experiments to evaluate and compare model performance using the ax CLI.
qec-autoresearch-skills
Guidance for selecting quantum error-correction decoder backends based on artifact shape, code family, noise model, and validation goals.
codescalebench
Launch, manage, and rerun CodeScaleBench benchmark suites with safety guardrails, paired baseline+full execution, and orchestration utilities.
skill-creator-claw
Create, test, and iteratively improve OpenClaw skills; includes eval workflows, test-case guidance, and packaging tools.
Awesome Omni Skill
Guided workflow for drafting, testing, and iterating Agent Skills: write SKILL.md, run evals, grade outputs, and improve descriptions to improve triggering accu
claude-superskills
Create, improve, and evaluate Agent Skills with a guided workflow: capture intent, draft SKILL.md, run evals and benchmarks, and optimize triggering description
ai-rig
Runs synthetic benchmarks and calibration tests for agents and skills: measures recall, precision, confidence calibration, and A/B comparisons to quantify instr
ide-agent-kit
Competitive puzzle arena API for AI agents: timed puzzles, per-model leaderboards, puzzle creation and moderation.
civic-analytics-agent-workflow-claude-skill
A master workflow for city policy analysis and civic innovation: frames problems, runs evidence-based analysis, crafts communications, benchmarks across cities,
dotfiles
Guides profiling and targeted optimizations for code and systems — measure, identify bottlenecks, and verify improvements across Python, Node, shell, and system
claude-plugins
Evaluation framework and tools for systematically measuring LLM performance using automated metrics, human judgment, and A/B testing.
claude-skill-registry
Guided performance analysis and profiling playbook for identifying bottlenecks and optimizing code, scripts, and systems across Python, Node.js, shell, and infr
gStack
Measure and detect performance regressions for web pages using automated benchmarks, baselines, and trend analysis.
jiuwenswarm
Drive the skvm CLI to profile models, AOT-compile skills, run single-task executions and benchmarks, and manage compilation/jit proposals via safe CLI workflows
skillattack
Extract, import, and add structured model evaluation results to Hugging Face model cards; run or import benchmark evaluations and generate model-index YAML for
opencode-skills-collection
Profile, analyze, and optimize Python applications for CPU and memory efficiency using profiling tools and performance best practices.
claude-skill-registry
Guidance and patterns for Python parallelism and GPU/CPU performance: threading vs multiprocessing vs asyncio, CUDA streams, PyTorch DDP, and benchmarking.
gstack-ko
Run automated performance baselines and regression detection for web pages (TTFB, FCP, LCP, bundle sizes, requests) and compare against historical baselines.
tao
Structured performance-audit methodology: measure, identify bottlenecks, optimize the true hotspot, and verify improvements with benchmarks.
OStack SaaS
Automated performance benchmarking and regression detection: captures baselines, measures Core Web Vitals, and compares metrics across PRs to flag regressions.
aec-bench
Interactively build and validate experiment.yaml configurations for AI benchmarks, including task and agent selection.
agentclash
Start, track, and analyze agent evaluation runs using the AgentClash CLI.
forkprobe
Compares multiple AI skills or pipelines side-by-side on a single task to determine the most effective output.
sage
Create, iterate on, and evaluate Agent Skills: write SKILL.md, design test cases, run benchmarks, and improve triggering and performance.
ako4all
Automated loop that profiles, iterates, benchmarks and commits GPU kernel optimizations across CUDA/Triton/TileLang/Python/C++ to achieve measurable speedups.
nemo-platform
Turn a domain rubric and dataset into a reproducible evaluation using the NeMo Evaluator SDK; generate configs, run local evaluations, and explain scores and fa
claude-skills
Setup and execute Mojo code within Claude.ai containers, including installation, compilation, and performance benchmarking.
awesome-codex-plugins
Compare AI agents (Claude Code, Codex, OpenCode) on real coding tasks using git worktrees and standardized checks.