Dag Convergence Monitor
Monitors directed acyclic graph (DAG) convergence, alerting when metrics indicate stability or divergence issues.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add dag-convergence-monitor npx -- -y @trustedskills/dag-convergence-monitor
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"dag-convergence-monitor": {
"command": "npx",
"args": [
"-y",
"@trustedskills/dag-convergence-monitor"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The dag-convergence-monitor skill allows an AI agent to monitor the convergence of Directed Acyclic Graphs (DAGs). It provides insights into the stability and progress of DAG-based processes, identifying potential issues before they impact downstream tasks. This is particularly useful for workflows involving complex dependencies and iterative refinement.
When to use it
- Debugging complex pipelines: Identify bottlenecks or instability in a workflow represented as a DAG.
- Monitoring iterative design processes: Track the convergence of designs or models evolving through multiple stages.
- Evaluating experimental setups: Assess the stability and reliability of experiments defined using DAGs.
- Optimizing resource allocation: Understand how resources are utilized across different nodes in a DAG to improve efficiency.
Key capabilities
- DAG Convergence Tracking
- Stability Analysis
- Progress Monitoring
- Dependency Visualization (implied)
Example prompts
- "Monitor the convergence of my data processing pipeline and alert me if it deviates significantly from expected behavior."
- "Analyze the stability of this design iteration DAG and identify potential areas for improvement.”
- “Show me a visualization of the resource utilization across all nodes in this experiment’s DAG.”
Tips & gotchas
The skill requires a properly formatted DAG representation as input, typically in JSON or similar structured format. Ensure your DAG is correctly defined to avoid inaccurate convergence analysis.
Tags
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