How does the pipeline differ from a standard Claude prompt?

Standard prompts are linear. Inference Planz uses specialized agents (Research, Survey, Plan) to break the task down, identify risks, and validate assumptions interactively before suggesting code changes.

Do I have to answer every survey question?

No. After the initial Research phase, you can select 'Accept All Recommended' to skip the detailed survey and proceed directly to the generated plan based on smart defaults.

Can I use this for existing codebases?

Yes. The skill uses tools like Read, Glob, and Grep to analyze your current project context during the Research phase to provide highly relevant implementation plans.

What is the Confidenz (CZ) Score?

The CZ Score is a specialized metric used by Inference Planz to indicate the AI's level of certainty regarding a specific task or question, helping you identify areas where requirements might be underspecified.

Inference Planz

Name: Inference Planz
Author: BLERBZ

byBLERBZ

Developer Tools

Orchestrates a high-precision multi-agent planning pipeline to transform complex prompts into actionable development roadmaps.

About

Inference Planz is a sophisticated workflow engine for Claude Code designed to eliminate ambiguity in software development tasks. By utilizing a three-stage pipeline—Research, Interactive Survey, and Planning—it forces a structured analysis of every request. The skill features a unique 'Confidenz' (CZ) scoring system that visually communicates the AI's certainty level, ensuring that users can make informed decisions through interactive UI elements before execution begins. It is the ideal companion for developers tackling complex refactors, new feature architectures, or deep debugging sessions where precision is paramount.

Key Features

Real-time Confidenz (CZ) scoring for risk assessment
Three-agent pipeline: Research, Survey, and Plan agents
Automated intent normalization and constraint detection
Interactive multi-choice surveys using Claude Code UI elements
0 GitHub stars
Production-grade roadmap generation with success criteria

Use Cases

Evaluating architectural trade-offs for new microservices or APIs
Standardizing the discovery phase of a project to ensure all constraints are met
Mapping out complex feature implementations from vague requirements

About

Key Features

Real-time Confidenz (CZ) scoring for risk assessment
Three-agent pipeline: Research, Survey, and Plan agents
Automated intent normalization and constraint detection
Interactive multi-choice surveys using Claude Code UI elements
0 GitHub stars
Production-grade roadmap generation with success criteria

Use Cases

Evaluating architectural trade-offs for new microservices or APIs
Standardizing the discovery phase of a project to ensure all constraints are met
Mapping out complex feature implementations from vague requirements