Analyzes sleep patterns and health data to provide personalized quality assessments and actionable improvement plans.
Framework for defining and implementing Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets.
You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based engineering…
Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for…
Comprehensive guide to tracking, calculating, and optimizing key performance metrics for different startup business models from seed…
Use when you need exact symbolic math in Python — algebra, calculus, equation solving, symbolic linear algebra, or code generation via…
FREE — Intelligent tool-call reliability wrapper.
Analyzes body composition, calculates metabolic rates, and manages weight loss progress through data-driven energy deficit tracking.
Integrate multiple digital health data sources, connect to [WellAlly.tech](https://www.wellally.tech/) knowledge base, providing data…
Searches, verifies, and delivers multi-angle analyses of corporate announcements across A-share, HKEX, and US SEC markets.
Use when positioning a Journal of Applied Econometrics (JAE) manuscript against prior work — applied-econometrics precedent, the methods…
Use when positioning a Journal of Business & Economic Statistics (JBES) methods paper against prior econometric and statistical methods.
Use for Livewire performance work. Covers what one Livewire request actually costs, the snapshot that travels both ways on every request…
llama.cpp local GGUF inference + HF Hub model discovery.
Implements layered resilience engineering, retry mechanisms, and self-healing pipelines for unattended LLM batch and scheduled jobs.
Use when: (1) Entering an LLM-based Kaggle competition (open-source model required, prompt engineering, few-shot), (2) Need to choose…
When to activate: LLM integration, LangChain, LlamaIndex, prompt templates, chains, tool calling, streaming, token budgeting, LLM caching…
Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK.
Investigate LLM output quality issues — trace hallucination root causes across context, retrieval, prompts, tool use, and workflow design
Configures structured JSON logging with Serilog (.NET) or structlog (Python).
Safely auto-detect the current machine's hardware (GPU, VRAM, system RAM, OS) with read-only commands, then recommend the top 3 local AI…