What are 'Reasoning Traces' in Scribe?

Every log entry must include a 'why', 'what', and 'how' block to explain the decision-making process, active constraints, and methodology used by the agent.

Which documents are managed by Scribe?

Scribe manages the core project suite including the ARCHITECTURE_GUIDE.md, PHASE_PLAN.md, and CHECKLIST.md files via the manage_docs tool.

What does the Scribe MCP skill do?

Scribe acts as a documentation guardrail for AI agents, ensuring they log implementation details every three edits and follow structured planning protocols.

How does Scribe prevent technical debt?

It enforces strict rules against creating parallel or replacement files, requiring agents to refactor and improve existing code directly within the current infrastructure.

Does Scribe support semantic search?

Yes, Scribe uses vector-based semantic retrieval to allow agents to find relevant entries in documentation and progress logs based on intent.

Scribe Documentation Governance

Name: Scribe Documentation Governance
Author: CortaLabs

byCortaLabs

Herramientas de Colaboración

Enforces documentation governance and auditability for AI agents by managing project structure, progress logging, and reasoning traces.

Acerca de

Scribe is a documentation governance system designed to keep AI agents aligned, accountable, and auditable while building software. It serves as a set of guardrails that prevents agents from bypassing existing infrastructure or losing implementation context. By requiring agents to log every significant decision using a 'Three-Part Framework' (Why, What, How), Scribe creates a persistent chain of reasoning. It automates the creation and maintenance of architecture guides, phase plans, and checklists, ensuring that all AI-driven development is traceable and follows established best practices.

Características Principales

Structured management of Architecture Guides, Phase Plans, and Checklists
Semantic search for retrieving project history and documentation context
Strict guardrails against technical debt and parallel file creation
Automated progress logging with mandatory reasoning traces (Why/What/How)
Readiness diagnostics via Scribe Doctor to validate repo and plugin status
0 GitHub stars

Casos de Uso

Maintaining an auditable trail of AI decision-making for compliance and debugging
Bootstrapping new software projects with standardized planning and architecture docs
Enforcing strict project management protocols across multi-agent AI workflows

Acerca de

Características Principales

Structured management of Architecture Guides, Phase Plans, and Checklists
Semantic search for retrieving project history and documentation context
Strict guardrails against technical debt and parallel file creation
Automated progress logging with mandatory reasoning traces (Why/What/How)
Readiness diagnostics via Scribe Doctor to validate repo and plugin status
0 GitHub stars

Casos de Uso

Maintaining an auditable trail of AI decision-making for compliance and debugging
Bootstrapping new software projects with standardized planning and architecture docs
Enforcing strict project management protocols across multi-agent AI workflows