Skill UI

This tool provides strategic legal guidance for founders and startup executives, covering critical areas like contract risk review (MSA, NDA, DPA), intellectual property strategy, term sheet decoding, and global regulatory compliance (GDPR, HIPAA, etc.). It surfaces key questions and potential traps to ensure thorough review before legal commitment. NOTE: This is not a substitute for licensed attorney advice.

Analyzes options chain data by separating real calls and puts from lottery-like speculative contracts to produce more reliable put/call sentiment, anomaly detection, and expiry breakdowns for watchlists, sectors, and event-driven names.

This skill provides comprehensive deal-desk support by performing quantitative scoring and risk assessment for commercial deals. It scores deals across margin, risk, and strategic value, routes discount requests to the correct human approver chain (e.g., Director, CFO, Legal), and flags contract landmines (e.g., uncapped indemnity, MFN) in redlined MSAs. It never auto-approves; every output is a score and a recommendation for a named human sign-off.

Invariant-Guard enforces a correctness-first approach to algorithm design. Instead of writing code and hoping it works, this skill mandates defining the function contract, loop invariants, termination arguments, and all potential edge cases *before* implementation. It is essential for complex algorithms where subtle bugs (like off-by-one errors or missed post-conditions) are common, ensuring mathematically rigorous and verifiable code.

A critical discipline for managing expenses when integrating paid AI or inference APIs. This guard treats dollar cost as a third complexity dimension, mandating the definition of cost contracts (max calls per run, max budget per run, max budget per day). It enforces best practices for bounding loops, retries, and fan-out, ensuring that code bugs cannot lead to unexpected overspending. Best practice requires configuring hard caps both in the code and at the provider dashboard for defense in depth.

This guide provides a systematic, safe workflow for refactoring rapidly developed or AI-generated fullstack applications. It focuses on identifying and removing dead code, fixing broken imports, and consolidating repetitive logic while strictly maintaining existing API contracts, routes, and core functionality. Use this before launch to ensure a stable, maintainable production baseline, following a 'surgery, not demolition' philosophy.

This meta-skill is designed for complex decision analysis when a user provides or references structured documents such as contracts, quotes, spreadsheets, or notices. Instead of simple summarization, it extracts key evidence, identifies risks (e.g., renewal risk, payment terms), and structures the output into decision-ready formats, such as 'sign/reject/negotiate' recommendations, evidence tables, or required next actions. It supports input from PDF, DOCX, and XLSX formats.

This meta-skill automates the complex process of modernizing legacy PDF documents (e.g., historical contracts, scanned manuals, legal documents). It follows a structured four-step pipeline: structural extraction, natural-language rewriting of problem pages, generating an audit summary, and finally re-merging the content into a single, refined PDF. This ensures content is modernized while maintaining fidelity to the original meaning, providing a human review summary before finalization.

An internal, language-agnostic probe designed for investigating complex stack traces when the source language is unknown. It analyzes the provided trace to output structured, language-neutral elements, including failure contract checks, minimal reproduction guidance, and specific patch targets. This tool is vital for robust failure analysis and debugging across diverse codebases.

An internal utility designed for deep investigation of JavaScript or TypeScript stack traces. It analyzes complex runtime errors, providing specific checks for asynchronous boundaries, module resolution issues, JSON parsing failures, and type contract violations. It aids developers by generating minimal reproduction commands and identifying potential patch targets for robust error handling.

This skill allows users to query the current state of various AWS resources (including EC2, S3, Lambda, RDS, VPC, etc.) using natural language. It translates user intent into strictly read-only AWS CLI commands (e.g., `describe-*`, `list-*`). Crucially, this tool can only view data and is contractually incapable of performing any write, modify, delete, or mutation actions, ensuring maximum safety.

Aria functions as a System Architect, responsible for establishing the definitive structural foundation of the entire system. She designs comprehensive blueprints covering the data model (schema, relationships, constraints), API contract specifications (endpoints, auth, pagination), modular file structure, and selection of core architectural design patterns. Her output ensures that no code is written without a rigorously defined, approved architectural plan, minimizing ambiguity and technical debt.