engineer-coder

Translate approved engineering handoffs into executable solution_script.py files.

2|Updated Jan 31, 2026
One-click install
npx skills add https://github.com/MRiabov/Problemologist-AI --skill engineer-coder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: engineer-coder
Source: https://github.com/MRiabov/Problemologist-AI/tree/main/.agents/skills/engineer-coder
Command: npx skills add https://github.com/MRiabov/Problemologist-AI --skill engineer-coder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Engineer Coder skill provides a stable operating manual for turning approved handoffs into concrete Python scripts, validations, simulations, and evidence inquiries, ensuring reproducible, contract-grounded engineering implementations.

Core Features & Use Cases

  • Converts engineering handoffs into runnable solution_script.py while preserving engineering_plan.md contracts.
  • Supports bounded retries, mechanism-pattern selection, validation, simulation, and render-evidence inspection.
  • Facilitates plan grounding in engineering_plan.md, frame-indexed objects.parquet evidence, and plan_refusal plan generation when infeasible.

Quick Start

Provide an approved handoff in engineering_plan.md and initiate the engineer-coder workflow to generate solution_script.py along with validation evidence.

Frequently Asked Questions about engineer-coder

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

FAQPage Schema
How do I automate approved engineering handoffs into validated Python scripts?▼

Automating engineering handoffs involves translating approved plans into an executable solution_script.py with validated revisions. The process preserves engineering_plan.md contracts while applying bounded retries, pattern selection, and simulation.

What is the best way to generate render-bundle evidence for CAD simulations?▼

Generating render-bundle evidence for CAD simulations requires querying frame-indexed objects.parquet data. This satisfies strict contract requirements and grounds results in engineering_plan.md anchors.

How does plan_refusal handling work when an engineering plan is infeasible?▼

Plan_refusal handling works by generating a refusal plan via plan_refusal.md when an engineering task is infeasible. It enforces strict evidence and contract requirements to reject handoffs that cannot be executed.

Do I need an engineering_plan.md file to start automating CAD solutions?▼

You need an approved engineering_plan.md file to start automating CAD solutions. This document provides the necessary contracts and anchors required to generate the solution_script.py and validation evidence.

Can I apply bounded retries and mechanism-pattern selection to engineering validation tasks?▼

You can apply bounded retries and mechanism-pattern selection to engineering validation tasks. The automation supports these mechanisms alongside simulation and render-evidence inspection to ensure robust solution revisions.

Why does engineering plan grounding require strict evidence and contract requirements?▼

Engineering plan grounding requires strict evidence and contract requirements to ensure reproducible, contract-grounded implementations. This prevents unverified handoffs from producing invalid solution_script.py outputs or incomplete validation data.