Claude-skill-registry diagnose-maestro-deployment

Diagnoses failed Maestro cluster deployments by analyzing Helm releases, pod status, and resource conflicts

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/diagnose-maestro-deployment" ~/.claude/skills/majiayu000-claude-skill-registry-diagnose-maestro-deployment && rm -rf "$T"

manifest: skills/data/diagnose-maestro-deployment/SKILL.md

Diagnose Maestro Deployment

Automatically diagnoses failed Maestro cluster deployments by:

Analyzing deployment output to identify resource groups and cluster names
Checking Helm release status in both service and management clusters
Inspecting pod states and error conditions
Identifying resource conflicts and timing issues
Generating a detailed analysis report with root cause and recommendations

Prerequisites:

Azure CLI installed and logged in
kubectl and kubelogin installed
Access to the failed deployment output or cluster information

Usage:

# Diagnose using deployment output file
diagnose-maestro-deployment /path/to/deployment.output

# Diagnose using cluster names directly
diagnose-maestro-deployment --svc-rg <resource-group> --svc-cluster <cluster-name> --mgmt-rg <resource-group> --mgmt-cluster <cluster-name>

#!/bin/bash
# Execute the diagnostic script
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
exec "$SCRIPT_DIR/scripts/diagnose.sh" "$@"