debugging-codegen-pipeline

Diagnose failures in the SEA codegen pipeline by tracing upstream specs, AST/IR, and manifests.

1|Updated Oct 1, 2025
One-click install
npx skills add https://github.com/GodSpeedAI/SEA --skill debugging-codegen-pipeline
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: debugging-codegen-pipeline
Source: https://github.com/GodSpeedAI/SEA/tree/main/.claude/skills/debugging-codegen-pipeline
Command: npx skills add https://github.com/GodSpeedAI/SEA --skill debugging-codegen-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps engineering teams diagnose and fix failures in the SEA codegen pipeline, ensuring deterministic outputs and faster remediation when specs, AST/IR, manifests, or last-mile steps diverge.

Core Features & Use Cases

  • Upstream tracing: identify whether issues originate from specs, AST/IR, or generator and map them to the appropriate fix.
  • Determinism stabilization: detect drift between regenerations and enforce upstream corrections.
  • Guided recovery: provide a repeatable workflow that validates inputs, re-runs the pipeline, and aligns artifacts without editing generated code.

Quick Start

Begin by validating the current context with the recommended checks and trace the failure to its source before attempting any regeneration.

Frequently Asked Questions about debugging-codegen-pipeline

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

FAQPage Schema
How do I fix a codegen pipeline when generated outputs are missing or incorrect?

To fix a codegen pipeline with missing or incorrect outputs, trace upstream artifacts like specs, AST/IR, and manifests to identify the source, validate inputs, and re-run the pipeline to align artifacts without editing the generated code directly.

Why does my codegen pipeline produce non-deterministic outputs between regenerations?

Codegen pipelines produce non-deterministic outputs due to drift in upstream artifacts. Detect this drift by comparing regenerated artifacts, then enforce upstream corrections in the specs or AST/IR rather than modifying the generated code.

What is the best way to trace codegen failures back to their source specs?

The best way to trace codegen failures to source specs is by following a guided recovery workflow that validates inputs, maps failures through AST/IR and manifests, and directs corrections upstream without touching generated code.

How do I stabilize a codegen pipeline that keeps failing during last-mile steps?

To stabilize a failing codegen pipeline, validate the current context with recommended checks, trace the failure to its source in the upstream artifacts, and re-run the pipeline after directing corrections to the specs or generator.

Can I edit generated code directly to fix a codegen pipeline failure?

You should not edit generated code directly to fix a codegen pipeline failure. Instead, enforce upstream corrections by validating inputs, re-running the pipeline, and comparing artifacts to ensure deterministic and traceable outputs.