abhishekmmgn

Chat completions using Sarvam AI LLMs (Sarvam-105B, Sarvam-30B). Handles AI chat, text generation, reasoning, coding, and multilingual conversations in Indian languages. OpenAI-compatible API. Use when building chatbots, Q&A systems, agents, or any LLM…

Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. (gstack)

Cross-model benchmark for gstack skills. (gstack)

Performance regression detection using the browse daemon. (gstack)

Fast headless browser for QA testing and site dogfooding. (gstack)

Post-deploy canary monitoring. (gstack)

OpenAI Codex CLI wrapper — three modes. (gstack)

Launch GStack Browser — AI-controlled Chromium with the sidebar extension baked in.

framework for implementing "Contract-Adhering Agents." Use this to define precise task specifications, deliverables, and negotiation loops to reduce ambiguity in complex workflows.

implementation patterns for Gemini agents. Use this for coding ReAct loops, defining tools in Python, and using frameworks like LangChain/LangGraph.

methodologies for assessing agent capabilities, tool-use trajectories, and final response quality. Use this to implement automated testing and human-in-the-loop validation for agents.

standardized protocols for agent collaboration. Use this to implement the Agent2Agent (A2A) protocol and Agent Cards to transform isolated agents into a collaborative ecosystem.

strategies for agent observability (logging, tracing, metrics). Use this to instrument agents for debugging, performance tracking, and quality assurance.

operationalization strategies for agents (AgentOps). Use this to manage internal/external tools, optimize agent "brain" prompts, and handle task decomposition.

operational strategy for continuous agent improvement. Use this to implement the "Flywheel" lifecycle: Define Quality, Instrument, Evaluate, and Architect Feedback Loops.

core framework for defining and measuring agent quality. Use this to shift from traditional software verification to agent validation using the "Outside-In" approach and the Four Pillars of Quality.

Diagnose and improve end-user web performance with measured evidence. Use whenever the user's primary goal is a faster website or web app: performance audits, Core Web Vitals, Lighthouse/PageSpeed regressions, slow loads or navigations, interaction lag,…

Use when implementing features or bug fixes where behavior should be specified before code. Applies best to new features, tricky logic, and high-correctness areas; avoid forcing it onto boilerplate, unstable spikes, or rapidly changing design work.