select-coder

Score coding tasks against a capability matrix to select optimal coder backends.

3|Updated May 7, 2026

Search Tags:#optimization #orchestration #ai-agent #model-selection #coding-workflow #capability-matrix

Ready to run

npx skills add https://github.com/bestdan/workflow-skills --skill select-coder

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: select-coder
Source: https://github.com/bestdan/workflow-skills/tree/main/skills/select-coder
Command: npx skills add https://github.com/bestdan/workflow-skills --skill select-coder

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill eliminates the guesswork in choosing an AI backend by objectively scoring tasks against a capability matrix, ensuring you always use the most cost-effective and capable model for your specific coding requirements.

Core Features & Use Cases

Capability Scoring: Evaluates tasks based on correctness, cost, speed, and autonomy requirements.
Availability Awareness: Probes local environment and auth status to ensure only runnable backends are recommended.
Use Case: When you have a complex architectural task, use this skill to determine if the current task requires the high-reasoning capabilities of a frontier model or if a cheaper, faster model is sufficient to handle the implementation.

Quick Start

Use the select-coder skill to recommend the best agent and model for implementing the new authentication module.

Frequently Asked Questions about select-coder

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

FAQPage Schema

How do I choose the optimal AI model for a specific coding task?▼

You can choose the optimal AI model by scoring task requirements like complexity and cost sensitivity against a capability matrix to find the most suitable agent backend. This ensures data-driven routing of coding tasks to the appropriate infrastructure.

How does automated AI agent selection work for programming workflows?▼

Automated AI agent selection works by probing your local environment and auth status to filter available backends, then scoring task correctness and autonomy needs against a capability matrix to recommend runnable models.

When do I need to use a frontier model instead of a cheaper model for implementation?▼

You need a frontier model when a complex architectural task requires high-reasoning capabilities and strict verification. A cheaper, faster model is sufficient when your coding workflow demands lower cost and speed over deep reasoning.

Can I use model selection for coding tasks if my local environment has limited agent backends?▼

Yes, you can use model selection with limited agent backends because the system probes local environment availability and auth status, ensuring it only recommends AI infrastructure that is actually runnable in your setup.

What is the best way to route coding tasks to the most appropriate AI infrastructure?▼

The best way to route coding tasks is to use a capability matrix that objectively scores correctness, cost, speed, and autonomy requirements against available agent backends, eliminating guesswork in choosing an AI backend.

Does the capability scoring approach work for tasks with high cost sensitivity and verification needs?▼

Yes, capability scoring works for high cost sensitivity and verification needs by evaluating these specific task requirements against the matrix to balance cost-effectiveness with the necessary model capabilities.