zreflect

Detect user instruction drift and generate gap analysis reports.

Updated Jul 29, 2026

Search Tags:#drift detection #self-reflection #AI feedback #project integrity #SSOT model

Ready to run

npx skills add https://github.com/2lab-ai/soma-work --skill zreflect

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: zreflect
Source: https://github.com/2lab-ai/soma-work/tree/main/src/local/skills/zreflect
Command: npx skills add https://github.com/2lab-ai/soma-work --skill zreflect

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

zreflect addresses the challenge of user drift during a coding session, ensuring that subsequent instructions align with the initial scope and maintaining project consistency.

Core Features & Use Cases

Drift Detection: Identifies when user instructions deviate from the initial scope.
Model Update: Applies a Hook to update the SSOT model accordingly.
Gap Analysis: Produces a report highlighting discrepancies between user intent and actions.
Feedback Loop: Evaluates and adjusts the AI's performance based on user feedback.

Quick Start

Initiate the self-reflection process after a re-instruction by executing the 'zreflect' command.

Frequently Asked Questions about zreflect

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

FAQPage Schema

How do I detect user instruction drift during an AI coding session?▼

Instruction drift is detected by monitoring user prompts against the initial project scope and generating a gap analysis report to highlight discrepancies between user intent and AI execution.

What is a gap analysis report for project integrity and when do I need it?▼

A gap analysis report for project integrity details the discrepancy between user intent and AI execution, needed when a re-instruction risks deviating from the initial SSOT model scope.

How do I maintain project consistency when instructions change mid-session?▼

To maintain project consistency when instructions change, execute a self-reflection process that monitors instruction drift and applies a Hook to update the SSOT model accordingly.

Do I need an SSOT model to use self-reflection for AI feedback?▼

Yes, you need an SSOT model and the ability to execute the 'local:using-ssot' Hook 2, as the self-reflection process requires access to update the model based on user feedback.

How does AI feedback evaluate performance after a re-instruction?▼

AI feedback evaluates performance by initiating a feedback loop after a re-instruction, adjusting the AI's execution to align with the updated SSOT model and reduce future instruction drift.