Skill UI

Simulates a highly structured, sequential peer-review process using multiple specialized AI agents (e.g., Skeptic, Constraint Guardian, User Advocate). This skill is designed to rigorously stress-test a design, surface hidden assumptions, identify potential failure modes, and enforce non-functional constraints before implementation. It transforms initial concepts into robust, validated specifications by simulating formal critique and achieving consensus via a mandatory Decision Log.

Apply a rigorous coding standard by explicitly stating assumptions, avoiding unsupported claims, and covering both happy and unhappy paths before writing or reviewing code to ensure reliability.

This skill generates a comprehensive, minimal, and enforceable security policy document (Blue Book) for applications handling sensitive data. It structures requirements using MUST/SHOULD/CAN language, explicitly defining assumptions, scope, threat models, and security gates. It is essential for establishing clear security guardrails and ensuring compliance early in the development lifecycle.

Delivers repository-grounded AppSec threat models that map components, boundaries, assets, entry points, and attacker capabilities to abuse paths, along with prioritized mitigations tailored to codebase evidence and explicit assumptions.

Verifies that blockchain code precisely implements documented specifications by comparing logic, invariants, flows, and assumptions against whitepapers or design documents, flagging undocumented behavior, mismatches, and compliance gaps during audit engagements.

A set of behavioral guidelines derived from Andrej Karpathy's observations to help users writing, reviewing, or refactoring code with Large Language Models (LLMs). It guides developers to avoid overcomplication, make surgical changes, explicitly surface assumptions, and define verifiable success criteria, promoting clean, simple, and robust code development.

Build interconnected Excel financial models (income statement, balance sheet, cash flow, DCF, cap table, scenarios) driven by an assumptions sheet so each output updates automatically from provided inputs.

Spec-Driven Development (SDD) is a structured methodology that mandates defining comprehensive specifications before writing any code. It guides users through a gated process: SPECIFY -> PLAN -> TASKS -> IMPLEMENT. This workflow ensures all assumptions are surfaced, requirements are concrete, and the final product has clear success criteria, minimizing ambiguity and architectural risk in large projects.

This meta-skill set provides a structured framework covering the entire software development lifecycle (SDLC). It guides developers through every phase, from initial concept refinement and requirement specification to incremental implementation, testing, code review, and deployment. It enforces critical professional behaviors like surfacing assumptions, managing ambiguity, and maintaining scope discipline to ensure high-quality, robust engineering outcomes.

Behavioral guidelines for writing, reviewing, and refactoring code with LLMs, emphasizing minimalism, clear assumptions, surgical edits, and verifiable success criteria to avoid common machine-assisted coding mistakes.

This skill guides the systematic execution of complex development plans. It mandates a critical review of the plan for dependencies, ambiguous conditions, and environmental assumptions before execution. The process involves incremental task completion, rigorous testing, structured committing, and final reporting, ensuring adherence to established development best practices.

This guide outlines a rigorous, technical framework for receiving and responding to code review feedback. It emphasizes that code review is a technical assessment, not an emotional exchange. Users learn how to verify assumptions, ask clarifying questions, professionally refute incorrect suggestions, and implement changes iteratively, ensuring code quality and architectural integrity.