GitHub
integration-testing
Integration testing patterns for APIs and components. Use when testing component interactions, API endpoints with test databases, or service layer integration.
☆ 98Voir le skill
Skills IA Documentation
Découvrez les skills Documentation, comparez leurs dépôts et consultez leurs instructions.
Catégories: Documentation
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Explorer
GitHub
evidence-verification
Use when completing tasks, code reviews, or deployments to verify work with evidence. Collects test results, build outputs, coverage metrics, and exit codes to prove work is complete.
☆ 98Voir le skill
GitHub
test-standards-enforcer
Enforce testing best practices - AAA pattern, naming conventions, isolation, coverage thresholds. Blocks non-compliant tests. Use when writing or reviewing tests.
☆ 98Voir le skill
GitHub
auth-patterns
Authentication and authorization patterns. Use when implementing login flows, JWT tokens, session management, password security, OAuth 2.1, Passkeys/WebAuthn, or role-based access control.
☆ 98Voir le skill
GitHub
owasp-top-10
OWASP Top 10 security vulnerabilities and mitigations. Use when conducting security audits, implementing security controls, or reviewing code for common vulnerabilities.
☆ 98Voir le skill
GitHub
defense-in-depth
Use when building secure AI pipelines or hardening LLM integrations. Defense-in-depth implements 8 validation layers from edge to storage with no single point of failure.
☆ 98Voir le skill
GitHub
error-handling-rfc9457
RFC 9457 Problem Details for standardized HTTP API error responses. Use when implementing problem details format, structured API errors, error registries, or migrating from RFC 7807.
☆ 98Voir le skill
GitHub
input-validation
Input validation and sanitization patterns. Use when validating user input, preventing injection attacks, implementing allowlists, or sanitizing HTML/SQL/command inputs.
☆ 98Voir le skill
GitHub
memory-fabric
Graph-first memory orchestration - knowledge graph (PRIMARY, always available) with optional mem0 cloud enhancement for semantic search. Use when designing memory orchestration or combining graph and mem0.
☆ 98Voir le skill
GitHub
off-policy-distillation
Generate training data from teacher models for off-policy distillation. Use when converting prompts to SFT datasets using larger models, generating teacher completions with tools, or preparing data for knowledg...
☆ 98Voir le skill
GitHub
rnow-tools
Write tool functions for ReinforceNow agent training. Use when creating @tool decorated functions, writing tools.py, or sandbox tools. Triggers on "@tool", "tools.py", "tool function", "function calling", "agen...
☆ 98Voir le skill
GitHub
rnow-rewards
Write reward functions for ReinforceNow RL training. Use when creating @reward decorated functions, writing rewards.py, using precondition rewards, sandbox rewards, llm_judge, or math-verify. Triggers on "rewar...
☆ 98Voir le skill
GitHub
add-golden
Curate and add documents to the golden dataset with multi-agent validation. Use when adding test data, creating golden datasets, saving examples.
☆ 98Voir le skill
GitHub
context-engineering
Use when designing agent system prompts, optimizing RAG retrieval, or when context is too expensive or slow. Reduces tokens while maintaining quality through strategic positioning and attention-aware design.
☆ 98Voir le skill
GitHub
pgvector-search
Production hybrid search combining PGVector HNSW with BM25 using Reciprocal Rank Fusion. Use when implementing hybrid search, semantic + keyword retrieval, vector search optimization, metadata filtering, or cho...
☆ 98Voir le skill
GitHub
llm-safety-patterns
Security patterns for LLM integrations including prompt injection defense and hallucination prevention. Use when implementing context separation, validating LLM outputs, or protecting against prompt injection a...
☆ 98Voir le skill
GitHub
load-context
Auto-load relevant memories at session start from both mem0 and graph. Use when you need session context restored or preloaded.
☆ 98Voir le skill
GitHub
langgraph-functional
LangGraph Functional API with @entrypoint and @task decorators. Use when building workflows with the modern LangGraph pattern, enabling parallel execution, persistence, and human-in-the-loop.
☆ 98Voir le skill
GitHub
function-calling
LLM function calling and tool use patterns. Use when enabling LLMs to call external tools, defining tool schemas, implementing tool execution loops, or getting structured output from LLMs.
☆ 98Voir le skill
GitHub
llm-streaming
LLM streaming response patterns. Use when implementing real-time token streaming, Server-Sent Events for AI responses, or streaming with tool calls.
☆ 98Voir le skill
GitHub
agent-loops
Agentic workflow patterns for autonomous LLM reasoning. Use when building ReAct agents, implementing reasoning loops, or creating LLMs that plan and execute multi-step tasks.
☆ 98Voir le skill
GitHub
langgraph-parallel
LangGraph parallel execution patterns. Use when implementing fan-out/fan-in workflows, map-reduce over tasks, or running independent agents concurrently.
☆ 98Voir le skill
GitHub
contextual-retrieval
Anthropic's Contextual Retrieval technique for improved RAG. Use when chunks lose context during retrieval, implementing hybrid BM25+vector search, or reducing retrieval failures.
☆ 98Voir le skill
GitHub
agentic-rag-patterns
Advanced RAG with Self-RAG, Corrective-RAG, and knowledge graphs. Use when building agentic RAG pipelines, adaptive retrieval, or query rewriting.
☆ 98Voir le skill
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.