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source-command-sparc-post-deployment-monitoring-mode

Monitors post-launch system performance, logs, and user feedback to flag regressions.

Updated May 11, 2026
Search Tags:#monitoring#observability#sparc#alerts#regression detection#claude-flow#post-deployment
One-click install
npx skills add https://github.com/Turgunoff/mebellar_app --skill source-command-sparc-post-deployment-monitoring-mode-turgunoff
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: source-command-sparc-post-deployment-monitoring-mode
Source: https://github.com/Turgunoff/mebellar_app/tree/main/.agents/skills/source-command-sparc-post-deployment-monitoring-mode
Command: npx skills add https://github.com/Turgunoff/mebellar_app --skill source-command-sparc-post-deployment-monitoring-mode-turgunoff

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? After a system goes live, teams need a structured way to observe production behavior, detect regressions early, and escalate issues before they impact users. This Skill provides a dedicated post-deployment monitoring role that collects metrics, logs, and feedback and turns them into actionable findings. ## Core Features & Use Cases - Metrics and Uptime Configuration: Sets up performance metrics, log collection, uptime checks, and alert thresholds for a deployed system. - Regression Detection: Flags regressions or unexpected behaviors and recommends improvements when thresholds are violated. - Escalation Workflow: Uses task delegation to escalate refactors or hotfixes and summarizes monitoring status upon completion. - Use Case: After shipping a new release, run this mode to watch production metrics, receive alerts when error rates exceed thresholds, and automatically escalate a hotfix task when a regression is confirmed. ## Quick Start Ask the assistant to run the post-deployment monitoring mode to watch production metrics and alert on any regressions after the latest release.

Frequently Asked Questions about source-command-sparc-post-deployment-monitoring-mode

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor production metrics after a deployment?▼

Run the post-deployment monitoring mode with a task description such as monitoring production metrics. It configures metrics, logs, uptime checks, and alerts, then flags regressions or threshold violations and summarizes findings.

How do I run a SPARC mode with claude-flow?▼

Use the MCP tool mcp__claude-flow__sparc_mode with the mode name and task description, or fall back to the NPX CLI command npx claude-flow sparc run followed by the mode name and task. A local installation can be invoked directly with ./claude-flow.

Can this monitoring mode escalate issues automatically?▼

Yes. When thresholds are violated or regressions are detected, it uses new_task to escalate refactors or hotfixes to other modes, then reports the monitoring status and findings with attempt_completion.

What tools does the post-deployment monitoring mode have access to?▼

It can use file reading and editing, web browsing, MCP tools, and command execution. These cover inspecting logs, adjusting configuration, and running diagnostic commands during monitoring.

When should I not use post-deployment monitoring mode?▼

It is designed for observing systems after launch, not for pre-release testing or active development. Use testing or debugging modes before deployment, and switch to this mode only once the system is live in production.

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