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graph-listening

Automate the mcp-graph LISTENING phase with DORA metrics and feedback analysis.

Updated Apr 26, 2026
Search Tags:#knowledge management#lifecycle management#DORA#feedback collection#retrospective analysis#mcp-graph
One-click install
npx skills add https://github.com/luissimon96/orchestration-devops-agents --skill graph-listening
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: graph-listening
Source: https://github.com/luissimon96/orchestration-devops-agents/tree/main/.agents/skills/graph-listening
Command: npx skills add https://github.com/luissimon96/orchestration-devops-agents --skill graph-listening

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The graph-listening Skill addresses the need for a structured approach to the LISTENING phase of the mcp-graph lifecycle, ensuring comprehensive feedback collection, data-driven analysis, and effective knowledge gap analysis for continuous improvement and cycle planning.

Core Features & Use Cases

  • DORA Retrospective Analysis: Automates the collection and analysis of DORA metrics for sprint performance review.
  • Cumulative Flow Analysis: Provides insights into flow patterns, WIP accumulation, and lead time distribution.
  • Knowledge Gap Analysis: Assesses the quality and coverage of documentation, identifying areas for improvement.
  • Sprint Metrics: Offers a detailed view of velocity trends, quality metrics, and estimation accuracy.
  • Feedback Collection: Integrates user feedback into actionable tasks.
  • Cross-Project Learnings: Incorporates insights from other team projects to enrich knowledge bases.
  • Retrospective Insights Recording: Stores insights from retrospectives for future reference.
  • Backlog Health Check: Reviews the backlog for orphan nodes, stale tasks, and priority distribution.
  • New PRD Creation: Facilitates the creation of new product requirements documents if necessary.
  • Lifecycle Phase Transition: Automates the transition to the next phase of the lifecycle based on feedback and analysis.

Quick Start

Activate the graph-listening Skill to initiate the LISTENING phase of the mcp-graph lifecycle.

Frequently Asked Questions about graph-listening

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

FAQPage Schema
How do I automate DORA metrics collection for sprint retrospective analysis?▼

Automating DORA retrospective analysis involves collecting deployment frequency and lead time metrics to review sprint performance. This Skill structures the LISTENING phase of the mcp-graph lifecycle to automate data collection and facilitate retrospective insights recording.

What is the best way to assess knowledge gaps and backlog health in software lifecycle management?▼

Assessing knowledge gaps and backlog health requires reviewing documentation coverage and scanning for orphan nodes or stale tasks. This Skill automates these evaluations during the mcp-graph LISTENING phase to identify areas for improvement and priority distribution.

How do I integrate user feedback into actionable tasks for cycle planning?▼

Integrating user feedback into actionable tasks requires collecting inputs and mapping them to follow-up actions. This Skill facilitates feedback collection and transforms insights into new tasks or product requirements documents for the next lifecycle phase.

Does graph-listening work with mcp-graph for cumulative flow and sprint velocity analysis?▼

Yes, graph-listening works with mcp-graph by requiring access to it and associated tools for analysis. It provides insights into cumulative flow patterns, WIP accumulation, lead time distribution, and detailed sprint velocity trends.

How do I transition to the next phase of the mcp-graph lifecycle after feedback collection?▼

Transitioning to the next lifecycle phase requires completing feedback processing and data-driven analysis. This Skill automates the lifecycle phase transition based on the evaluated DORA metrics, backlog health, and collected retrospective insights.

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