Assess multi-agent network health by analyzing scratchpads, git diffs, and delegation efficiency.
npx skills add https://github.com/bert-berkers/UrbanRepML --skill ego-check
Please help me install this Agent Skill. Skill: ego-check Source: https://github.com/bert-berkers/UrbanRepML/tree/main/.claude/skills/ego-check Command: npx skills add https://github.com/bert-berkers/UrbanRepML --skill ego-check
This Skill provides a comprehensive assessment of the AI agent's operational health, identifying areas of friction and proactively planning for future development sessions.
Run the ego-check skill to assess the current agent process health.
High-intent search queries and answers about installing and using this skill.
To assess multi-agent network health, you evaluate node and edge connections, scratchpad meaningfulness, and delegation efficiency to identify strained processes and operational friction.
Agent self-assemblage is the process of detecting gaps in a multi-agent network to proactively coordinate and plan the integration of new agents for future development sessions.
You evaluate agent scratchpads and git diffs by analyzing specifications versus implementation to identify working areas, strained processes, and overall operational health metrics.
Yes, you can detect coordination gaps by evaluating lateral coordination and supra-coordinator communication quality, allowing you to plan next steps before starting a new sprint.
You should run a process assessment for multi-agent coordination before starting a new development sprint to ensure all agents are communicating effectively and to generate a clear roadmap.
Metrics indicating strained processes in a multi-agent system include poor delegation efficiency, incoherent agent scratchpads, and degraded lateral coordination and supra-coordinator communication quality.
FrantssCompare git diffs against repository standards and project specifications.
markus41Facilitate Scrum ceremonies and manage sprint backlog with agile estimation.
getdooverCoordinates multi-agent data flows via channels, tags, and UI states.
TheBushidoCollectiveEvaluate code diffs across correctness, safety, maintainability, testability, performance, and standards.
