ai coding partner

The problem

General coding assistants often produce generic code that ignores your project conventions, uses hallucinated APIs, or skips complex implementation details with "TODO" stubs.

What it does

• Scans dependency files and project structure to auto-detect your specific tech stack and naming conventions.
• Drafts a detailed implementation plan and flags architectural risks before writing a single line of code.
• Writes production-ready logic without placeholders, respecting existing error handling and import patterns.
• Allows injection of five custom constraints for performance, security, or backward compatibility requirements.

Frameworks & tools

Language agnostic. Works with Node.js, Go, Rust, Python, and any project containing standard dependency manifests like package.json or requirements.txt.

Why this beats prompting it yourself

Instead of manually feeding context to an LLM, this skill automates the discovery of your repo standards. It enforces a "plan-then-code" workflow that prevents the agent from diving into incorrect implementations or breaking your existing API contracts.

Use cases

• Adding complex features to large legacy codebases while maintaining style consistency.
• Scaffolding new services with specific performance and security constraints.
• Refactoring monolithic functions into clean, decoupled middleware or modules.
• Implementing new API endpoints that must adhere to strict backward compatibility rules.

Known limitations

Relies on conventional file names for stack detection. Does not perform automatic git commits, requiring manual review of all changes.