rust-performance-analyzer
Analyzes Rust code for performance bottlenecks, memory inefficiencies, and optimization opportunities. Use when discussing performance, slow code, memory usage, profiling, benchmarks, or optimization.
Découvrez les skills content media llm ai, comparez leurs dépôts et consultez leurs instructions.
Analyzes Rust code for performance bottlenecks, memory inefficiencies, and optimization opportunities. Use when discussing performance, slow code, memory usage, profiling, benchmarks, or optimization.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when "installing spaCy", "selecting model for nlp" (en_core_web_sm/md/lg/trf), "tokenization", "POS tagging", "name...
Synthesize consensus implementation plan from multi-agent debate reports using external AI review
Guide for distinguishing Claude Code features (Commands, Skills, Agents, Hooks, Rules) and selection criteria. Use when decomposing context files, deciding where to add new features, or customizing Claude Code.
Master model serving - inference optimization, scaling, deployment, edge serving
Expert guidance on 9 programming languages and 10+ frameworks. Compare, select, and master language ecosystems.
Systematic vulnerability finding, threat modeling, and attack surface analysis for AI/LLM security assessments
Implement mitigations, create input filters, design output guards, and build defensive prompting for LLM security
Tools and frameworks for AI red teaming including PyRIT, garak, Counterfit, and custom attack automation
Generate adversarial inputs, edge cases, and boundary test payloads for stress-testing LLM robustness
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment
Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning
Securing AI/ML infrastructure including model storage, API endpoints, and compute resources
Implementing safety filters, content moderation, and guardrails for AI system inputs and outputs
Security best practices for deploying AI/ML models to production environments
Advanced prompt manipulation including direct attacks, indirect injection, and multi-turn exploitation
Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods
Test AI systems for code injection vulnerabilities including prompt-to-code attacks and agent exploitation
Techniques to extract model weights, architecture, and training data through API queries
Master prompt injection attacks, jailbreak techniques, input manipulation, and payload crafting for LLM security testing
Standard datasets and benchmarks for evaluating AI security, robustness, and safety
Delegate user perspective reviews to GPT-5.2 Reviewer agent. Use when (1) Feature implementation is complete and needs UX validation, (2) User asks to create a pull request (review before PR), (3) User explicit...
Delegate simple, fast tasks to GPT-5-mini Quick-Helper agent. Use when (1) Simple file operations needed (finding files, listing directories, basic grep), (2) Quick validations required (file existence, JSON va...
Monitor and analyze narrative API logs from Google Cloud Run. Use when (1) Investigating Cloud Run API errors or failures, (2) Analyzing API usage costs and optimizing spend, (3) Measuring scenario generation p...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.