Can it help with AI/ML model monitoring?

Yes, it is designed to establish performance baselines during the development phase and monitor for deviations or drift during operational phases.

What happens when a metric breaches a threshold?

It triggers an escalation workflow that includes updating the risk register, notifying the owner, and defining a corrective action plan with a specific timeline.

What types of metrics can this skill track?

It covers four main categories: Delivery (velocity, cycle time), Quality (defect density, coverage), AI/ML (drift, latency), and Governance (gate pass rate, artefact completion).

Is this skill compatible with standard agile ceremonies?

Absolutely. It specifically includes triggers for sprint reviews, gate reviews, and phase-start baselining to fit into existing agile workflows.

How does it handle missing data?

The skill follows a strict 'no guessing' policy; any data gaps are documented as project risks rather than being estimated or interpolated.

Agile Metrics & Quality Tracking

Name: Agile Metrics & Quality Tracking
Author: nsalvacao

bynsalvacao

0•

Analytics & Monitoring

Collects, calculates, and reports on sprint performance, product quality, and AI model health to ensure data-driven delivery governance.

This skill empowers Claude to act as a data-driven delivery manager by identifying, measuring, and analyzing critical KPIs across the software development lifecycle. It standardizes the collection of delivery, quality, and AI/ML metrics—such as velocity, defect density, and model drift—while comparing them against pre-defined thresholds to trigger escalations or corrective actions. By automating the generation of sprint records and gate reports, it ensures stakeholders receive objective insights into project health and process compliance while maintaining a clear audit trail in the evidence index.

Key Features

01Automated threshold monitoring with warning and breach classification

02Integration with evidence indexes and risk registers for corrective action

03AI/ML model drift and latency tracking against established baselines

04Standardized calculation of delivery, quality, and AI/ML metrics

050 GitHub stars

06Comprehensive reporting for sprint reviews and governance gate packages

Use Cases

01Conducting governance gate reviews to ensure artefact completion and quality targets

02Monitoring AI model performance post-deployment for drift or latency issues

03Generating a comprehensive sprint review report after team completion

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nsalvacao/nsalvacao-claude-code-plugins metrics-tracking

For use in Claude.ai and ChatGPT

Key Features

01Automated threshold monitoring with warning and breach classification

02Integration with evidence indexes and risk registers for corrective action

03AI/ML model drift and latency tracking against established baselines

04Standardized calculation of delivery, quality, and AI/ML metrics

050 GitHub stars

06Comprehensive reporting for sprint reviews and governance gate packages

Use Cases

01Conducting governance gate reviews to ensure artefact completion and quality targets

02Monitoring AI model performance post-deployment for drift or latency issues

03Generating a comprehensive sprint review report after team completion

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nsalvacao/nsalvacao-claude-code-plugins metrics-tracking

For use in Claude.ai and ChatGPT