find-model-fit-conversational

Interviews users about work habits to recommend a fitting AI model family.

Updated Jul 16, 2026
One-click install
npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill find-model-fit-conversational-cloud-byte-consulting
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: find-model-fit-conversational
Source: https://github.com/Cloud-Byte-Consulting/plugins/tree/main/prompt-workflows/skills/find-model-fit-conversational
Command: npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill find-model-fit-conversational-cloud-byte-consulting

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Choosing an AI model based on benchmark rankings often leads to a poor match with how a person actually works. This Skill runs a structured guided interview that maps your real working style to the model family that fits it, plus a backup model and a falsifiable test of the recommendation. ## Core Features & Use Cases - Guided Interview: Asks an open-ended opening question followed by four targeted follow-ups, one at a time, with sharpening questions when answers are vague. - Work Fingerprint Analysis: Synthesizes your answers into a three-sentence profile of how you actually get to good work. - Model Family Recommendation: Names one of two model families (briefer or finder style), a second model for specific situations, and a two-week falsifiable test. - Use Case: A consultant unsure whether to use a long-brief model or an exploratory model talks through a recent project for five minutes and receives a concrete recommendation tied to their own examples, not leaderboard scores. ## Quick Start Use the find-model-fit-conversational skill to interview me about how I work and recommend which AI model family fits me best.

Frequently Asked Questions about find-model-fit-conversational

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

FAQPage Schema
How do I choose an AI model based on my working style?

Describe a recent hard piece of work, what drains you, and how you give instructions to AI. The interview maps those answers to one of two model families: briefer-style models for precise instruction following, or finder-style models for exploratory work.

What is the difference between briefer and finder model families?

Briefer-style models suit people who know what they want upfront and need literal instruction following and exact correction obedience. Finder-style models suit people whose hard part is figuring out what the thing even is, reading between the lines before drafting.

Does this interview recommend specific model versions or subscriptions?

No. The interview names only a model family, never a specific version or subscription tier. It also avoids benchmarks, rankings, and leaderboard scores, grounding the recommendation only in what you say about your work.

What happens if both model families fit my work style?

The output names both families and states what would break the tie rather than forcing a single verdict. It also identifies a second model and the concrete situation where it takes over from the primary.

How do I know if the model recommendation is wrong?

The output includes a section called The Tell: one falsifiable sentence describing how you will know within two weeks whether the recommendation is wrong, based on your own described work patterns.