deep-trace

Trace cross-layer data flows across C#, Rust, and React to verify field names, types, and serialization.

2|1|Updated Dec 10, 2025
One-click install
npx skills add https://github.com/inernoro/prd_agent --skill deep-trace
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-trace
Source: https://github.com/inernoro/prd_agent/tree/main/.claude/skills/deep-trace
Command: npx skills add https://github.com/inernoro/prd_agent --skill deep-trace

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

对不信任的跨层代码变更进行端到端穿透式验证,逐层核对字段名、类型、序列化规则与异常处理,确保链路完整。

Core Features & Use Cases

  • 接缝扫描与链路穿透:在 C#、Rust、前端 React 等层之间逐步验证字段名、类型和序列化规则的一致性。
  • 合同校验:确保前后端输入输出契约符合约定,降低运行时的字段错配风险。
  • 边界测试:通过边界场景与错误路径验证系统鲁棒性,及早发现潜在问题。

Quick Start

运行深度追踪以对最新变更执行端到端数据流穿透分析,获得跨层数据穿越的完整报告。

Frequently Asked Questions about deep-trace

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I trace data flow across frontend and backend layers to verify field names and types?

Cross-layer data tracing verifies field names, types, and serialization rules across frontend React, Rust, and C# layers. It scans seams between layers to ensure end-to-end data consistency and compliance with API contracts.

Why do my frontend and backend fields mismatch after serializing data across Rust and C# layers?

Field mismatches during serialization often occur at layer boundaries. Cross-layer tracing validates serialization formats and input/output contracts across Rust, C#, and React to detect field name and type discrepancies early.

How do I validate API contract compliance across multi-language stacks spanning services and UI boundaries?

Validating API contracts across multi-language stacks requires end-to-end data flow verification. Cross-layer tracing checks input/output compliance, serialization formats, and error-handling paths across C#, Rust, and React boundaries.

Does cross-layer data tracing work with React, Rust, and C# stacks for boundary testing?

Cross-layer data tracing works across React, Rust, and C# stacks for boundary testing. It validates error-handling paths and boundary scenarios across all layers to verify system robustness and detect potential issues.

When should I run end-to-end data flow validation on code changes spanning APIs and UI?

Run end-to-end data flow validation when changes span APIs, services, and UI boundaries in multi-language stacks. Deep tracing analyzes cross-layer data flows to verify field consistency and serialization across seams.

What is the best way to verify serialization consistency across C#, Rust, and React layers?

The best way to verify serialization consistency is cross-layer tracing, which progressively checks field names, types, and serialization rules across C#, Rust, and React seams to ensure end-to-end contract compliance.