Performance
Performance profiling and optimization
context-engineering
by vibery-studio
Master context engineering for AI agents - token optimization, degradation patterns, compression, memory systems, multi-agent coordination, evaluation. Use when designing agents, debugging context failures, or building LLM pipelines.
functional-constructs-types
by marius-townhouse
Use when building arrays in loops. Use when types don't flow through code. Use when considering map/filter/reduce.
spice-ai
by spiceai
Add AI and LLM capabilities to Spice — chat completions, text-to-SQL (NSQL), tool use, memory, and model routing. Use when configuring language models, enabling tools (SQL, search, MCP, web search), setting up NSQL, adding conversational memory, configuring model fallback or load balancing, or using the OpenAI-compatible API.
angular-typescript-cursorrules-prompt-file-cursorrules
by Tryboy869
"Apply for angular-typescript-cursorrules-prompt-file. --- description: General rules for Angular components, focusing on code quality, performance, and maintainability. globs: */.component.ts"
spice-acceleration
by spiceai
Accelerate data locally for sub-second query performance. Use when enabling data acceleration, choosing an engine (Arrow, DuckDB, SQLite, Cayenne), configuring refresh modes, setting up retention policies, creating snapshots, adding indexes, or materializing datasets.
axolotl
by tylertitsworth
"Axolotl — config-driven LLM fine-tuning framework. YAML-based SFT, instruction tuning, chat fine-tuning, DPO/IPO/KTO/ORPO preference optimization, GRPO reinforcement learning, reward modeling, LoRA/QLoRA, full fine-tuning with FSDP/DeepSpeed multi-GPU, N-D Parallelism (TP+CP+FSDP composition), multimodal VLM training, text diffusion training, QAT with NVFP4, sample packing, Flash Attention, dataset preprocessing, and checkpoint management. Use when fine-tuning or post-training LLMs with Axolotl."
wp-performance
by peixotorms
Use when optimizing WordPress performance, debugging slow queries, configuring caching, reviewing database code, or preparing for high traffic. Covers WP_Query optimization (get_posts, meta_query, tax_query, no_found_rows, update_post_meta_cache, fields), object cache (wp_cache_get, wp_cache_set, Redis, Memcached), transients (set_transient, get_transient), autoload options, Query Monitor, Debug Bar, slow query profiling, anti-patterns (posts_per_page -1, query_posts, N+1), WP-CLI profiling, asset loading strategies, and platform-specific guidance.
using-perplexity-for-context
by designnotdrum
"Automatically use Perplexity search for personalized context enrichment. Use when facing unfamiliar technologies, decision points, learning questions, or preference-dependent choices."
spice-models
by spiceai
Configure AI/LLM model providers in Spice (OpenAI, Anthropic, Azure, Google, xAI, Bedrock, Perplexity, Databricks, local models). Use when asked to "add a model", "configure LLM", "set up OpenAI", "add language model", "enable chat completions", "serve local model", "add AI gateway", or "configure system prompt".
spice-accelerators
by spiceai
Configure data accelerators for local materialization and caching in Spice (Arrow, DuckDB, SQLite, Cayenne, PostgreSQL, Turso). Use when asked to "accelerate data", "enable caching", "materialize dataset", "configure refresh", "set up local storage", "improve query performance", "choose an accelerator", or "configure snapshots".
ultrathink
by thoreinstein
Ultra-deep multi-perspective analysis for complex architectural and strategic decisions requiring systematic reasoning across technical, business, user, and system perspectives
deepagents-cli
by christian-bromann
Using the Deep Agents CLI - terminal interface, persistent memory with AGENTS.md, project conventions, skills directories, and CLI commands.
rust-performance
by peixotorms
Use when optimizing Rust code performance. Covers profiling with flamegraph and perf, benchmarking with criterion, allocation analysis with dhat, Arc, Rc, Cow, SmallVec, arena allocation, zero-copy, SIMD, cache locality, #[inline], LTO, codegen-units, buffer reuse, collection choice, iterator optimization, string optimization, Rayon parallelism, struct memory layout, and release build settings.
system-check
by dgriffin831
Check system health and performance
image-compress-skill
by 994AK
A production-grade, Rust-powered image optimization engine for AI Agents. Smartly routes between PNG quantization and WebP compression.
github-user
by Mearman
Get GitHub user profile information including repos, followers, and activity. Use when the user asks for GitHub user details, profile information, or developer stats.
standards
by weegigs
Manage project standards. Auto-detects state and offers appropriate actions.
sixhats
by askarzh
This skill should be used when the user asks to "use six hats", "apply six thinking hats", "think with different hats", "use De Bono's hats", "separate thinking modes", "look at this from all angles", "consider all perspectives", or wants to process input through Edward de Bono's Six Thinking Hats to systematically examine a topic from multiple cognitive perspectives.
swiftui-development
by ProjAnvil
Specialized in building user interfaces using modern SwiftUI, covering NavigationStack, Observation framework, and SwiftData integration.
learning-about-you
by designnotdrum
"Proactively learn about the user through onboarding and ongoing observation. Use at session start and when you notice potential preferences."
memory-scan
by dgriffin831
Safe to run frequently (minimal API cost with efficient chunking)
database-indexing
by 1Mangesh1
Database indexing strategies and query optimization. Use when user asks to "optimize queries", "create indexes", "database performance", "query analysis", "explain plans", "index selection", "slow queries", "database tuning", "schema optimization", or mentions database performance and query optimization.
growth-development
by pluginagentmarketplace
Master career development, engineering ladders, IDPs, succession planning, and mentoring for engineering teams
deepagents-memory
by christian-bromann
Implementing long-term memory in Deep Agents with cross-session storage using StoreBackend, CompositeBackend, and InMemoryStore for persistent data.