su-reconcile

Detect discrepancies in AI-native documentation and coordination files.

17|2|Updated Jun 2, 2026
One-click install
npx skills add https://github.com/SeemSeam/agent-roles-spec --skill su-reconcile
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: su-reconcile
Source: https://github.com/SeemSeam/agent-roles-spec/tree/main/roles/su-ccb/skills/su-reconcile
Command: npx skills add https://github.com/SeemSeam/agent-roles-spec --skill su-reconcile

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

The su-reconcile skill addresses the problem of discrepancies between documentation, coordination files, and console projections in AI-native environments, providing an automated process to identify and repair issues based on approved actions.

Core Features & Use Cases

  • AI Self-Assessment: Detects discrepancies between source documentation, coordination files, and console projections.
  • Automated Repair: Executes repairs based on pre-approved actions to resolve identified issues.
  • Use Case: When inconsistencies are detected between documentation and coordination files, this skill can be triggered to automatically repair these discrepancies and maintain data integrity.

Quick Start

To run the AI self-assessment for reconcile, use the command: /ccb:su-reconcile --payload {"scope":"project","mode":"detect"}

Frequently Asked Questions about su-reconcile

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

FAQPage Schema
How do I detect discrepancies between documentation and coordination files in AI-native environments?▼

To detect discrepancies in AI-native environments, run an AI self-assessment using the reconcile command with a detect mode payload. This identifies inconsistencies between source documentation, coordination files, and console projections.

What is automated repair for data integrity in project documentation?▼

Automated repair for data integrity is a process that executes pre-approved actions to resolve inconsistencies detected between documentation and coordination files. It ensures consistency by fixing discrepancies based on user approvals.

Can I automatically fix console alignment issues after identifying discrepancies?▼

Yes, you can fix console alignment issues after identifying discrepancies by executing repair actions. The skill detects misalignments between console projections and documentation, then applies repairs based on user approvals.

Do I need to manually approve repairs for coordination file inconsistencies?▼

Yes, repairs for coordination file inconsistencies require user approvals before execution. The skill identifies discrepancies and then executes repair actions only after they are pre-approved, maintaining secure data integrity.

When should I run an AI self-assessment for documentation reconciliation?▼

You should run an AI self-assessment for documentation reconciliation when inconsistencies are suspected between source documentation and coordination files. It is triggered to identify and repair discrepancies, maintaining data integrity.