Skill UI

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

A specialized review tool for identifying critical performance bottlenecks within Django applications. It focuses on validating issues such as N+1 queries, unbounded querysets, missing database indexes, and write loops. Use this when you suspect database slowdowns or memory exhaustion due to inefficient ORM usage, ensuring findings are provable and actionable.

Master common data transformations using functional programming patterns in TypeScript. This guide covers essential techniques for arrays, objects, and complex data structures, including mapping, filtering, reducing, grouping, and safely accessing nested values. It teaches how to replace verbose, imperative loops with concise, declarative functional code, improving readability and maintainability.

This skill provides a systematic methodology for iteratively improving complex skill documentation. By utilizing a reviewer agent, it identifies and categorizes issues (Critical, Major, Minor) in a structured loop. The process ensures that the skill meets high standards of quality, reliability, and functional completeness before deployment, moving beyond simple manual edits.

Autonomous frontend builders follow a Stitch-driven baton loop to read prompts, generate and integrate pages, refresh documentation, and hand off the next task for continuous site evolution.

This skill manages complex coding tasks from initial implementation through testing, review incorporation, deployment, and final runtime verification. It ensures the task meets explicit Definition of Done (DoD) criteria iteratively, minimizing the need for manual prompting across multiple development stages.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Autoresearch Agent runs an autonomous optimization loop that edits a target file, invokes a provided evaluation command, keeps metric-improving commits, drops failures, and repeats indefinitely so engineers can optimize speed, bundle size, prompts, or other measurable goals overnight.

Starts a recurring autoresearch experiment loop at user-selected intervals (10 minutes to monthly), auto-schedules CronCreate jobs, records experiment metadata, and offers commands to monitor progress or stop the loop.

This skill automates the iterative process of improving a written academic paper. It simulates an advanced peer review cycle (Review → Fix → Recompile) using an external LLM (GPT-5.4) over multiple rounds. It fixes theoretical inconsistencies and enhances presentation quality, going beyond simple review to actively refine the manuscript.

Autonomously run programs, analyze outputs, and iteratively tune parameters for computer architecture and EDA workloads until objectives or timeouts are reached, making it easy to request sweeps, optimizations, or best configurations.

This skill orchestrates a complete, multi-stage pipeline for academic paper writing. It takes a raw narrative report or research idea and systematically guides the user through planning, figure specification, LaTeX drafting, compilation, and an automated improvement loop. It is designed to transform unstructured research notes into a polished, submission-ready academic manuscript with full source code and PDF output.