AuraHQ.ai
Official@aurahq-ai
AuraHQ provides specialized infrastructure for managing trace observability, codebase self-modification, and performance benchmarking for production-grade software development environments.
Agent Skills by AuraHQ.ai
Showing 5 vetted skills indexed across 1 GitHub repositories.
AuraHQ-ailangfuse
Query and manage Langfuse traces, prompts, datasets, scores, and sessions via CLI.
AuraHQ-aiaura-self-modification
Guide Aura to read, modify, and improve her own codebase through structured PR workflows.
AuraHQ-aiaura-bench-local-iteration
Automate local memory-bench iterations for Cursor Cloud Agents against Neon DB.
AuraHQ-aiaura-deployment
Deploy Aura to Vercel, manage environment variables, and configure Slack app.
AuraHQ-aiaura-memory-bench
Benchmark Aura's memory extraction, retrieval, and QA pipeline against production-like timelines.
Frequently Asked Questions About AuraHQ.ai
FAQPage SchemaWhat specific tasks can be performed using AuraHQ?▼
AuraHQ enables the management of Langfuse traces, prompts, and datasets while facilitating codebase self-modification through structured pull requests. It supports benchmarking memory extraction and retrieval pipelines against production-like timelines and handles deployment configurations for Vercel environments.
Which technical personas benefit from these capabilities?▼
These capabilities are designed for software engineers and infrastructure developers focused on observability, performance benchmarking, and iterative codebase maintenance. It is particularly suited for teams managing complex retrieval pipelines and those requiring automated validation of memory extraction performance.
What are the primary dependencies for running these benchmarks?▼
Benchmarking requires a configured Neon DB instance and integration with Cursor Cloud environments. Deployment tasks necessitate an active Vercel account and Slack workspace permissions for environment variable management and notification routing.