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AIS-Commercial-Business-Unit
AIS-Commercial-Business-UnitOFFICIAL
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ais.report.metrics

Generate outcome metrics reports from repository state and GitHub metadata.

Updated Jul 1, 2026
Search Tags:#project management#repository analysis#spec-driven engineering#metrics reporting#engineering delivery
One-click install
npx skills add https://github.com/AIS-Commercial-Business-Unit/CBU_Specify --skill ais-report-metrics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ais.report.metrics
Source: https://github.com/AIS-Commercial-Business-Unit/CBU_Specify/tree/main/.cursor/skills/ais.report.metrics
Command: npx skills add https://github.com/AIS-Commercial-Business-Unit/CBU_Specify --skill ais-report-metrics

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the generation of comprehensive outcome metrics reports, providing valuable insights into the performance and efficiency of spec-driven engineering delivery processes.

Core Features & Use Cases

  • Outcome Metrics Reporting: Collects and analyzes data on delivery speed, predictability, review quality, rework, traceability, methodology adoption, and delivery economics.
  • Repo State Analysis: Gathers repository state information, including Git history, GitHub metadata, project plan artifacts, and previous metrics reports.
  • Metrics Model Building: Constructs a detailed metrics model based on the gathered data, including cycle time, delivery predictability, PR acceptance rate, defect escape rate, rework rate, spec adherence rate, traceability coverage, and cost per delivered feature.
  • Report Generation: Outputs a comprehensive report with executive summary, board-level outcome view, operating metrics view, adoption and governance indicators, per-metric calculation table, evidence sources and limitations, data gaps, and instrumentation backlog.

Quick Start

Run the /ais.report.metrics skill to generate an outcome metrics report for your project.

Frequently Asked Questions about ais.report.metrics

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

FAQPage Schema
How do I generate engineering delivery metrics from Git history and GitHub metadata?▼

To generate engineering delivery metrics, this skill analyzes your repository state, Git history, and GitHub metadata to build a detailed metrics model covering delivery speed, predictability, and review quality. It outputs a comprehensive outcome metrics report for spec-driven engineering delivery.

What outcome metrics are included in a spec-driven engineering delivery report?▼

Spec-driven engineering delivery reports include cycle time, delivery predictability, PR acceptance rate, defect escape rate, rework rate, spec adherence rate, traceability coverage, and cost per delivered feature. These metrics provide insights into review quality, methodology adoption, and delivery economics.

Do I need project plan artifacts to generate delivery economics and predictability reports?▼

Yes, generating delivery economics and predictability reports requires access to project plan artifacts alongside repository data and GitHub metadata. The skill gathers these artifacts to construct an accurate metrics model for your engineering delivery outcome reporting.

What is the best way to report on traceability coverage and methodology adoption for engineering projects?▼

The best way to report on traceability coverage and methodology adoption is to automate metrics model building from repository state and project plan artifacts. This approach generates a board-level outcome view with per-metric calculation tables and evidence sources.

How does repository state analysis handle data gaps and instrumentation backlog in metrics reporting?▼

Repository state analysis identifies data gaps and maintains an instrumentation backlog by gathering Git history, GitHub metadata, and previous metrics reports. The generated report explicitly documents evidence sources, limitations, and missing instrumentation required for complete delivery economics tracking.

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