GraphQL Services Refactoring Surgeon Workshop
A safe refactor plan for GraphQL services: characterization tests, seams, and steps that keep CI green. Built for platform teams working in GraphQL services, tuned for ChatGPT. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
Preview
You are a staff engineer who has maintained large GraphQL services in production for years.
Inputs you will receive:
Stack: {{STACK}}
Feature: {{FEATURE}}
Codebase context: {{CODEBASE_CONTEXT}}
… [purchase to unlock the full framework]Screenshots
Example outputs
OrderService.calculate() takes the tax client directly — introduce TaxProvider interface here to cut the AWS dependency…
Ran this for a GraphQL services project with only the placeholders filled — the structure held and the output needed light edits only. (ChatGPT)
Version history
- v1Initial releaseJul 10, 2026
Buyers get every future update free.
Buyers also bought
Paste a slow query and schema — get back an optimized version, index recommendations, and a plain-English explanation of why it was slow.
Safely refactor gnarly legacy code: characterization tests first, seams identification, strangler-fig migration plan. Based on real enterprise migration experience.
A disciplined build-a-feature workflow for REST APIs: plan first, tests first, small diffs. Built for agency dev shops working in REST APIs, tuned for Cursor. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
A safe refactor plan for machine-learning services: characterization tests, seams, and steps that keep CI green. Built for platform teams working in machine-learning services, tuned for Windsurf. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
More from Marco Vance
A thorough review pass tuned for Python backends — correctness first, style last. Built for startup engineering teams working in Python backends, tuned for ChatGPT. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
Meaningful test coverage for CLI tools — behavior tests, edge cases and fixtures that stay maintainable. Built for startup engineering teams working in CLI tools, tuned for ChatGPT. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
A disciplined build-a-feature workflow for legacy Java systems: plan first, tests first, small diffs. Built for startup engineering teams working in legacy Java systems, tuned for Cursor. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
A structured way to make and document architecture calls for internal dashboards. Built for platform teams working in internal dashboards, tuned for Cursor. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
Reviews
No reviews yet.