GitHub
openai-image-gen
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
Skills IA tools llm ai
Découvrez les skills tools llm ai, comparez leurs dépôts et consultez leurs instructions.
Catégories: tools llm ai
tools llm ai Effacer les filtres
Explorer
GitHub
collaborating-with-coco
Delegates coding tasks to Coco CLI (Codebase Copilot) for prototyping, debugging, and code review. Use when needing algorithm implementation, bug analysis, or code quality feedback. Supports multi-turn sessions...
GitHub
ms-docs-researcher
Search and retrieve official Microsoft documentation, code samples, and technical information. Use PROACTIVELY when researching Azure AI Search, Copilot Studio, Azure Cognitive Services, Azure App Service, Micr...
GitHub
agent-memory
Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'...
GitHub
spec-builder
Generate comprehensive specification documents including requirements, technical design, and detailed task breakdown from any feature request. Use when the user asks to create specs, requirements docs, design d...
GitHub
skill-builder
Comprehensive guide for building Agent Skills according to agentskills.io specification. Use when developers need to create, structure, or validate skills that follow the Agent Skills standard format and best p...
GitHub
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.
GitHub
using-spacy-nlp
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...
GitHub
external-consensus
Synthesize consensus implementation plan from multi-agent debate reports using external AI review
GitHub
claude-code-features
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.
GitHub
model-serving
Master model serving - inference optimization, scaling, deployment, edge serving
GitHub
languages-frameworks
Expert guidance on 9 programming languages and 10+ frameworks. Compare, select, and master language ecosystems.
GitHub
vulnerability-discovery
Systematic vulnerability finding, threat modeling, and attack surface analysis for AI/LLM security assessments
GitHub
defense-implementation
Implement mitigations, create input filters, design output guards, and build defensive prompting for LLM security
GitHub
red-team-frameworks
Tools and frameworks for AI red teaming including PyRIT, garak, Counterfit, and custom attack automation
GitHub
adversarial-examples
Generate adversarial inputs, edge cases, and boundary test payloads for stress-testing LLM robustness
GitHub
safety-filter-bypass
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment
GitHub
rag-exploitation
Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning
GitHub
infrastructure-security
Securing AI/ML infrastructure including model storage, API endpoints, and compute resources
GitHub
input-output-guardrails
Implementing safety filters, content moderation, and guardrails for AI system inputs and outputs
GitHub
secure-deployment
Security best practices for deploying AI/ML models to production environments
GitHub
prompt-hacking
Advanced prompt manipulation including direct attacks, indirect injection, and multi-turn exploitation
GitHub
llm-jailbreaking
Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods
GitHub
code-injection
Test AI systems for code injection vulnerabilities including prompt-to-code attacks and agent exploitation
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.