Does this skill work with any programming language?

Yes. The Analyzer is designed to be source-agnostic; it identifies the language structure from the source path and maps common constructs to a standardized IR format.

What is an Intermediate Representation (IR)?

An IR is a language-neutral format that describes the behavior, control flow, and logic of a codebase without using the syntax of a specific programming language. It serves as a universal blueprint for migration.

Can it document external API dependencies?

Absolutely. It captures full HTTP request/response shapes, headers, authentication methods, and retry patterns to ensure external integrations are fully documented for the migration process.

How does the Analyzer handle ambiguous or complex code?

The skill follows a strict 'zero inference' policy. If a behavior is unclear, it uses explicit 'unknown' tokens rather than guessing, ensuring the output is reliable and traceable to the source.

Intermediate Representation Analyzer

Name: Intermediate Representation Analyzer
Author: augentic

byaugentic

0•

开发者工具

Generates a reconstruction-grade, language-agnostic Intermediate Representation (IR) of source code logic to streamline cross-language migrations.

The Analyzer skill is a specialized tool for legacy code modernization and cross-platform migration. It extracts pure business logic from a source codebase and transforms it into a standardized, language-agnostic Intermediate Representation (IR). By stripping away language-specific syntax and infrastructure noise, the skill focuses on control flows, data transformations, and domain rules. This produces a high-fidelity, reconstruction-grade blueprint that developers can use to rebuild applications in any target runtime—such as moving from Python to Go or Java to Rust—ensuring that critical behavioral nuances and edge cases are preserved without being biased toward a specific implementation.

主要功能

010 GitHub stars

02High-fidelity capture of async patterns, timing, and retry logic

03Language-agnostic Intermediate Representation (IR) generation

04Component-level tracing with domain, infrastructure, and mechanical tagging

05Automated domain-level business logic extraction

06Detailed mapping of external API surfaces and service dependencies

使用场景

01Porting legacy monolithic backends to modern microservices in different languages

02Auditing and documenting undocumented business rules for compliance and security

03Creating architectural blueprints for large-scale refactoring and system redesigns

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add augentic/plugins analyzer

For use in Claude.ai and ChatGPT

Download Skill