For advanced optimization techniques including NumPy vectorization, caching, memory management, parallelization, async I/O, database optimization, and benchmarking tools, see references/advanced-patterns.md. Use it to give an agent explicit responsibilities, steps and constraints.
Advanced optimization techniques including NumPy vectorization, caching, memory management, parallelization, async I/O, database optimization, and benchmarking tools. Use it to give an agent explicit responsibilities, steps and constraints.
This skill assumes finetuning-method-selection already routed here because the data shape is preference pairs or unpaired thumbs-up/down feedback, not demonstrations (that's lora-qlora-recipes) or a verifiable reward signal (that's grpo-rlvr-training). What follows is metho. Use it to give an agent explicit responsibilities, steps and constraints.
1. Establish Baseline : Always measure initial performance 2. Change One Thing : Isolate variables for clear attribution 3. Test Thoroughly : Use diverse, representative test cases 4. Track Metrics : Log all experiments and results 5. Validate Significance : Use st. Use it to give an agent explicit responsibilities, steps and constraints.
sql-optimization-patterns — detailed patterns and worked examples captures reusable agent playbook guidance for testing & documentation. Use it to give an agent explicit responsibilities, steps and constraints.
Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis. Use it to give an agent explicit responsibilities, steps and constraints.
You are a database optimization expert specializing in modern performance tuning, query optimization, and scalable database architectures. Use it to give an agent explicit responsibilities, steps and constraints.
You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, GCP, and OCI. Where provi. Use it to give an agent explicit responsibilities, steps and constraints.
spark-optimization — detailed patterns and worked examples captures reusable agent playbook guidance for research & evaluation. Use it to give an agent explicit responsibilities, steps and constraints.
You are a PR optimization expert specializing in creating high-quality pull requests that facilitate efficient code reviews. Generate comprehensive PR descriptions, automate review processes, and ensure PRs follow best practices for clarity, size, and reviewability. Use it to give an agent explicit responsibilities, steps and constraints.
Strategies and patterns for optimizing cloud costs across AWS, Azure, GCP, and OCI. Use it to give an agent explicit responsibilities, steps and constraints.
You MUST follow these rules exactly. Violating any of them is a failure. Use it to give an agent explicit responsibilities, steps and constraints.
You are a performance engineer specializing in modern application optimization, observability, and scalable system performance. Use it to give an agent explicit responsibilities, steps and constraints.
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration. Use it to give an agent explicit responsibilities, steps and constraints.
This file covers how to design prompt-building code for effective caching. For language-specific syntax, see the Prompt Caching section in each language's README or single-file doc. Use it as a repeatable review, validation or hardening pass.
TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), and Direct Preference Optimization (DPO). Built on top of the 🤗 Transformers ecosystem, TRL supports. Use it to navigate the topic and choose relevant methods, papers or tools.
GeoCalib is an algorithm for single-image calibration: it estimates the camera intrinsics and gravity direction from a single image only. By combining geometric optimization with deep learning, GeoCalib provides a more flexible and accurate calibration compared to previous approaches.
The main purpose of this tool is to automate image optimization and analysis. This project is recent, so use it with care, I'm listening to all feedback (we can talk via [twitter][twitter], don't follow me I never tweet).
For advanced optimization techniques including NumPy vectorization, caching, memory management, parallelization, async I/O, database optimization, and benchmarking tools, see references/advanced-patterns.md. Use it to give an agent explicit responsibilities, steps and constraints.
Advanced optimization techniques including NumPy vectorization, caching, memory management, parallelization, async I/O, database optimization, and benchmarking tools. Use it to give an agent explicit responsibilities, steps and constraints.
This skill assumes finetuning-method-selection already routed here because the data shape is preference pairs or unpaired thumbs-up/down feedback, not demonstrations (that's lora-qlora-recipes) or a verifiable reward signal (that's grpo-rlvr-training). What follows is metho. Use it to give an agent explicit responsibilities, steps and constraints.
1. Establish Baseline : Always measure initial performance 2. Change One Thing : Isolate variables for clear attribution 3. Test Thoroughly : Use diverse, representative test cases 4. Track Metrics : Log all experiments and results 5. Validate Significance : Use st. Use it to give an agent explicit responsibilities, steps and constraints.
sql-optimization-patterns — detailed patterns and worked examples captures reusable agent playbook guidance for testing & documentation. Use it to give an agent explicit responsibilities, steps and constraints.
Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis. Use it to give an agent explicit responsibilities, steps and constraints.
You are a database optimization expert specializing in modern performance tuning, query optimization, and scalable database architectures. Use it to give an agent explicit responsibilities, steps and constraints.
You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, GCP, and OCI. Where provi. Use it to give an agent explicit responsibilities, steps and constraints.
spark-optimization — detailed patterns and worked examples captures reusable agent playbook guidance for research & evaluation. Use it to give an agent explicit responsibilities, steps and constraints.
You are a PR optimization expert specializing in creating high-quality pull requests that facilitate efficient code reviews. Generate comprehensive PR descriptions, automate review processes, and ensure PRs follow best practices for clarity, size, and reviewability. Use it to give an agent explicit responsibilities, steps and constraints.
Strategies and patterns for optimizing cloud costs across AWS, Azure, GCP, and OCI. Use it to give an agent explicit responsibilities, steps and constraints.
You MUST follow these rules exactly. Violating any of them is a failure. Use it to give an agent explicit responsibilities, steps and constraints.
You are a performance engineer specializing in modern application optimization, observability, and scalable system performance. Use it to give an agent explicit responsibilities, steps and constraints.
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration. Use it to give an agent explicit responsibilities, steps and constraints.
This file covers how to design prompt-building code for effective caching. For language-specific syntax, see the Prompt Caching section in each language's README or single-file doc. Use it as a repeatable review, validation or hardening pass.
TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), and Direct Preference Optimization (DPO). Built on top of the 🤗 Transformers ecosystem, TRL supports. Use it to navigate the topic and choose relevant methods, papers or tools.
GeoCalib is an algorithm for single-image calibration: it estimates the camera intrinsics and gravity direction from a single image only. By combining geometric optimization with deep learning, GeoCalib provides a more flexible and accurate calibration compared to previous approaches.
The main purpose of this tool is to automate image optimization and analysis. This project is recent, so use it with care, I'm listening to all feedback (we can talk via [twitter][twitter], don't follow me I never tweet).