What is the primary goal of the Phoenix Precision Guard skill?

The primary goal is to ensure mathematical accuracy and type safety in high-priority financial calculation files by enforcing Decimal.js usage and strict TypeScript/ESLint configurations.

Does it support XIRR or fee logic bug fixes?

While it improves the underlying math safety, specific logic bugs in XIRR or fees should be handled by the specialized phoenix-xirr-fees-validator skill.

How does it handle existing TypeScript errors?

It prioritizes fixing errors in P0 files while allowing non-critical issues to be baselined with @ts-expect-error comments for phased resolution.

Which files are targeted by this skill?

It targets P0 calculation paths including XIRR, waterfall analytics, fees, capital allocation, exit recycling, and core financial utilities.

Can I use this for general UI logic?

No, this skill is specifically scoped for calculation engines and analytics modules where precision is critical; it is not intended for general UI or non-financial logic.

Phoenix Precision Guard

Name: Phoenix Precision Guard
Author: nikhillinit

bynikhillinit

Analytics & Monitoring

Enforces strict numeric precision and type safety across critical financial calculation paths within the Phoenix VC fund model.

About

Phoenix Precision Guard is a specialized engineering skill designed to harden the mathematical reliability of financial analytics by replacing imprecise native JavaScript operations with robust Decimal.js implementations. It automates the identification and replacement of legacy parseFloat calls, configures strict TypeScript and ESLint rules for critical P0 files, and establishes centralized precision standards to prevent rounding errors in high-stakes calculations like XIRR and waterfall distributions. This tool is essential for developers maintaining complex fund models who need to ensure absolute data integrity and regression-free refactoring.

Key Features

0 GitHub stars
Automated triage and replacement of parseFloat with Decimal.js in P0 analytics paths
Centralized Decimal.js configuration and dedicated precision validation testing
Incremental enforcement of strict TypeScript flags including strictNullChecks and noImplicitAny
Custom ESLint rules to ban implicit type coercion and enforce explicit radix usage
Regression monitoring to ensure truth-case pass rates remain stable after refactors

Use Cases

Hardening financial engines against floating-point errors in VC fund calculations
Migrating legacy analytics code to strict TypeScript and Decimal.js standards
Auditing and refactoring P0 modules for XIRR, fees, and capital allocation

About

Key Features

0 GitHub stars
Automated triage and replacement of parseFloat with Decimal.js in P0 analytics paths
Centralized Decimal.js configuration and dedicated precision validation testing
Incremental enforcement of strict TypeScript flags including strictNullChecks and noImplicitAny
Custom ESLint rules to ban implicit type coercion and enforce explicit radix usage
Regression monitoring to ensure truth-case pass rates remain stable after refactors

Use Cases

Hardening financial engines against floating-point errors in VC fund calculations
Migrating legacy analytics code to strict TypeScript and Decimal.js standards
Auditing and refactoring P0 modules for XIRR, fees, and capital allocation