darwin

What problem does it solve?

This Skill automates the detection of project lifecycle phases, assesses the health and relevance of AI agents within an ecosystem, and proposes evolutionary actions to improve overall system fitness and adapt to project changes.

Core Features & Use Cases

• Ecosystem Health Assessment: Continuously monitors and scores the health of your AI agent ecosystem using metrics like Coverage, Coherence, Activity, Quality, and Adaptability.
• Lifecycle Phase Detection: Automatically identifies the current phase of a project (e.g., GENESIS, ACTIVE_BUILD, PRODUCTION) based on git, file, and activity signals.
• Agent Relevance Scoring: Evaluates how relevant each agent is to the current project context and flags underused or outdated agents.
• Evolutionary Proposals: Suggests concrete actions for ecosystem improvement, such as agent refinement, new skill creation, or retiring obsolete agents.
• Use Case: When your development team notices a slowdown in feature delivery, Darwin can analyze the agent ecosystem, detect if the project has shifted into a 'STABILIZATION' phase, and recommend agents that are more suited for maintenance and quality assurance, while flagging agents that are no longer relevant.

Quick Start

Use the darwin skill to assess the current health of the AI agent ecosystem.