Kano Model Feature Prioritization Agent

activev1.0.0

Classifies product features using the Kano Model and generates a prioritized development roadmap with Berger Coefficient of Satisfaction (CS) and Coefficient of Dissatisfaction (DS) scores. Given a product description and list of candidate features, orchestrates hub-and-spoke multi-agent handoffs to survey classification, Berger coefficient computation, and roadmap synthesis. Methodology based on Matzler & Hinterhuber (1998, Technovation), doi:10.1016/S0166-4972(97)00020-0.

by Test Researcher

#kano-model#product-management#feature-prioritization#roadmap#berger-coefficients

MIT

Source Code

View on GitHub

76d8b0b

Publication

10.1016/S0166-4972(97)00020-0

MCP Endpoint

https://citedagents.com/api/agents/bcacc04d-33c5-4fbc-8da9-e22ebf4415d9/mcp

JSON-RPC 2.0 — POST with tools/list or tools/call

Key Files

main.py — CLI entrypoint — reads JSON from stdin or file, orchestrates agents, writes output JSON and HTML report

orchestrator.py — Hub orchestrator agent — routes to classification and analysis sub-agents via handoffs

classification/agent.py — Classification sub-agent — maps features to Kano categories (Must-be, One-dimensional, Attractive, Indifferent, Reverse)

classification/schema.py — Pydantic models for KanoClassificationInput and KanoClassificationOutput

classification/prompts.py — System prompt embedding Kano survey question pairs and classification rules

analysis/agent.py — Analysis sub-agent — computes Berger CS/DS coefficients and prioritizes the feature roadmap

analysis/schema.py — Pydantic models for KanoAnalysisInput, KanoAnalysisOutput, and RoadmapOutput

analysis/prompts.py — System prompt for Berger coefficient calculation and roadmap generation

report/renderer.py — Jinja2-based HTML report renderer for the Kano analysis output

report/template.html — Jinja2 HTML template for the Kano feature prioritization report

Property	Type	Required	Description
features	array	yes	List of candidate features to classify and prioritize
product_name	string	yes	Name of the product being analyzed (e.g., "TaskFlow Pro")
target_market	string	no	Optional: description of the target customer segment
product_description	string	yes	Brief description of the product and its intended use case

Dependencies

python: openai-agents>=0.0.3python: pydantic>=2.0.0python: jinja2>=3.1.0

Cite this Agent

Test Researcher. (2026). Kano Model Feature Prioritization Agent (v1.0.0) [AI Agent]. Cited Agents. https://doi.org/10.1016/S0166-4972(97)00020-0

Scientific References

DOI10.1016/S0166-4972(97)00020-0

Matzler & Hinterhuber (1998) — How to make product development projects more successful by integrating Kano's model of customer satisfaction into quality function deployment. Technovation, 18(1), 25–38.