GitHub
user-journey-tracking
Track user journeys with intent context and friction signals. Use when instrumenting onboarding, checkout, or any multi-step flow where you need to understand WHY users fail.
☆ 100Voir le skill
nexus-labs-automation AI Skills
GitHub ↗Explorez les skills IA publiés de nexus-labs-automation et consultez leurs instructions source.
Statistiques de l’auteur
Skills indexés
42Étoiles des dépôts des skills indexés
850Forks du dépôt
80Moyenne des étoiles par skill indexé
20Les étoiles d’un dépôt peuvent se répéter entre ses skills.
Catégories populaires
Indexation récente
Explorer
GitHub
symbolication-setup
Configure crash symbolication for readable stack traces. Use when setting up dSYMs (iOS), ProGuard/R8 mappings (Android), or source maps (React Native).
☆ 100Voir le skill
GitHub
session-replay
Set up session replay for visual debugging. Use when implementing screen recording, replay features, or visual debugging tools.
☆ 100Voir le skill
GitHub
crash-instrumentation
Set up crash instrumentation with actionable context. Use when configuring crash capture, error boundaries, or breadcrumb strategies.
☆ 100Voir le skill
GitHub
interaction-latency
Measure time from user tap to action completion. Use when tracking button response times, form submissions, add-to-cart, or any tap-triggered operation.
☆ 100Voir le skill
GitHub
instrumentation-planning
Plan what to measure in mobile apps. Use when starting observability, prioritizing instrumentation, or asking "what should I track?"
☆ 100Voir le skill
GitHub
network-tracing
Instrument API requests with spans and distributed tracing. Use when tracking request latency, correlating client-backend traces, or debugging API issues.
☆ 100Voir le skill
GitHub
navigation-latency
Measure time from navigation tap to screen fully loaded and interactive. Use when tracking screen transitions, deep links, or tab switches.
☆ 100Voir le skill
GitHub
prompt-versioning
Track prompt versions, A/B test variants, and measure prompt performance
GitHub
guardrails-safety
Instrument safety checks, content filters, and guardrails for agent outputs
GitHub
instrumentation-planning
Plan what to measure in AI agent systems using tiered approach
GitHub
human-in-the-loop
Instrument human approval workflows, feedback loops, and escalations
GitHub
session-conversation-tracking
Instrument sessions, conversations, and multi-turn interactions
GitHub
token-cost-tracking
Track token usage and costs across agents for budget management
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production-eval-strategy
Strategies for evaluating agents in production - sampling, baselines, and regression detection
GitHub
evaluation-quality
Instrument evaluation metrics, quality scores, and feedback loops
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error-retry-tracking
Instrument error handling, retries, fallbacks, and failure patterns
GitHub
multi-agent-coordination
Instrument multi-agent workflows, handoffs, and parent-child relationships
GitHub
llm-call-tracing
Instrument LLM API calls with proper spans, tokens, and latency
GitHub
memory-rag-instrumentation
Instrument RAG retrieval, memory operations, and context management
GitHub
decision-tracing
Trace agent decision-making, tool selection, and reasoning chains
GitHub
tool-call-tracking
Instrument agent tool executions with proper context and error handling
GitHub
database-observability
Instrument database queries, connection pools, and detect N+1 queries
GitHub
health-checks
Implement liveness, readiness, and dependency health checks
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.