What is the primary benefit of the Convo skill?

The Convo skill ensures total alignment between the user and the AI, preventing wasted time on incorrect approaches and ensuring that context is never lost during long or complex sessions.

Does this skill create files in my project repository?

Yes, it can create structured markdown files in directories like 'convo-captures/' and 'convo-exits/' to provide a permanent record of decisions and session progress.

When should I trigger a 'Capture' phase?

You should use the Capture phase mid-conversation when a significant decision is made, a major block of work is completed, or when you need to pause the session and resume it later.

Can I bypass the full alignment phase for small tasks?

Yes, the skill is designed to skip full alignment for simple questions or when you provide explicit instructions to proceed immediately, keeping your workflow fast.

How does the 'Start' protocol prevent errors?

The Start protocol requires the AI to state its understanding and propose a plan before writing any code, allowing you to correct misunderstandings before work begins.

Conversation Lifecycle Manager

Name: Conversation Lifecycle Manager
Author: violetio

byvioletio

生産性とワークフロー

Manages the complete lifecycle of AI interactions through structured alignment, context capture, and performance debriefing.

概要

The Convo skill provides a standardized framework for managing complex interactions within Claude Code, ensuring every task begins with clear alignment, maintains context through mid-session checkpoints, and concludes with a structured debrief. By implementing formal Start, Capture, and Exit phases, it eliminates ambiguity during task initialization and prevents context loss during long development sessions. This skill is essential for maintaining continuity across handoffs, documenting architectural decisions, and establishing a feedback loop that continuously improves the AI's performance within your specific codebase.

主な機能

Structured debriefing protocols to summarize outcomes and identify remaining tasks
Standardized documentation templates for session handoffs and architectural records
Phase-based alignment to confirm goals and technical approaches before execution
Automated mid-conversation context captures to prevent data loss during long sessions
Systematic feedback loops to capture user preferences and improve future interactions
0 GitHub stars

ユースケース

Managing long-running engineering features that require multiple decision points and checkpoints
Creating a persistent audit trail of architectural decisions and changes made during a coding session
Handing off complex work sessions between different developers or AI instances without context loss

概要

主な機能

Structured debriefing protocols to summarize outcomes and identify remaining tasks
Standardized documentation templates for session handoffs and architectural records
Phase-based alignment to confirm goals and technical approaches before execution
Automated mid-conversation context captures to prevent data loss during long sessions
Systematic feedback loops to capture user preferences and improve future interactions
0 GitHub stars

ユースケース

Managing long-running engineering features that require multiple decision points and checkpoints
Creating a persistent audit trail of architectural decisions and changes made during a coding session
Handing off complex work sessions between different developers or AI instances without context loss