Input is processed only in the active browser tab's memory and is not sent to a ByteQuant server.
Hallucination Risk Checklist
Turn claim verification, sourcing, freshness, and uncertainty checks into a task-specific list. It provides explainable preparation and evaluation without calling a remote model; it neither generates nor verifies model output.
Output will appear here. Load the example to try the tool immediately.
Input and output are not stored. The optional usage counter keeps only tool identity and count, never content.
Output comes from disclosed rules or browser APIs and needs independent review before high-impact use.
A result in three steps
- 01
Enter the goal and constraints.
- 02
Run the local evaluation.
- 03
Test the result against the real model and sources.
When is this tool useful?
- ✓ AI workflow preparation
- ✓ Context and risk planning
- ✓ Output evaluation
Automated output is a preliminary assessment. Do not use it alone for legal, financial, medical, or security-critical decisions.
Guides for this tool
Source Quality, Context Priority, and Hallucination Control for RAG
Choose better evidence, clearer instructions, and traceable claims instead of merely more context.
Read guide →Verifiable Workflow Planning with Local Agent and Workstation
Turn an outcome into a tool order, safety boundary, and reversible nodes.
Read guide →Frequently asked questions
Does this tool send input to a server?+
No. Processing runs in this browser tab. Data leaves the page only when you choose to copy or download the result.
Is the result definitive?+
The tool produces consistent output from disclosed rules and browser APIs, but context, data quality, and method limitations can affect it. Verify high-impact decisions.
Is input saved?+
No. Tool input is not persisted. With consent, only tool identity and usage count may be kept on this device for personal shortcuts.