Where is the configuration data stored?

The settings are saved in a file named .claude/confidenz.config.json within your project directory.

Can I disable logging for security reasons?

Yes, history logging can be turned off at any time using the 'log off' argument to ensure inference data is not stored locally.

What does the Inference Confidenz skill do?

It allows you to configure how Claude Code displays and logs the confidence levels associated with its generated output and actions.

How do I see the current status of my settings?

You can use the command /inference-confidenz:configure status to see your current display and logging configuration.

What is the benefit of detailed display mode?

Detailed mode provides additional context regarding the specific level of confidence, which is helpful for debugging why an AI might be hesitant about a specific code change.

Inference Confidenz Configuration

Name: Inference Confidenz Configuration
Author: BLERBZ

byBLERBZ

Analíticas y Monitorización

Manages the display and logging settings for AI inference confidence levels within the Claude Code environment.

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The Inference Confidenz configuration skill provides developers with granular control over how Claude reports its internal certainty during task execution. By allowing users to toggle confidence displays, switch between minimal and detailed metadata views, and enable history logging, this skill enhances the observability of the AI's decision-making process. It is particularly useful for teams who need to audit AI performance or want a cleaner CLI workspace by suppressing or expanding inference metrics.

Características Principales

Persistent settings storage via project-level JSON configuration
Enable or disable local history logging for inference data
Switch between minimal and detailed reporting formats
0 GitHub stars
Check current configuration status with a single command
Toggle visibility of AI confidence scores

Casos de Uso

Monitoring AI certainty during complex refactoring tasks to identify high-risk changes
Creating an audit trail of AI confidence levels for compliance and quality assurance
Customizing the CLI interface to reduce visual noise while maintaining access to inference data

Acerca de

Características Principales

Persistent settings storage via project-level JSON configuration
Enable or disable local history logging for inference data
Switch between minimal and detailed reporting formats
0 GitHub stars
Check current configuration status with a single command
Toggle visibility of AI confidence scores

Casos de Uso

Monitoring AI certainty during complex refactoring tasks to identify high-risk changes
Creating an audit trail of AI confidence levels for compliance and quality assurance
Customizing the CLI interface to reduce visual noise while maintaining access to inference data