core-metrics

Capture pipeline completion metrics and persist them to metrics.yaml.

Updated Aug 23, 2026

Search Tags:#analytics #validation #schema #metrics #yaml #pipeline #storage

Ready to run

npx skills add https://github.com/daniyarseifolla/agent-skills --skill core-metrics

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: core-metrics
Source: https://github.com/daniyarseifolla/agent-skills/tree/main/v2.2/core/metrics
Command: npx skills add https://github.com/daniyarseifolla/agent-skills --skill core-metrics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Pipeline teams spend cycles collecting, validating, and recording execution data after jobs finish. core-metrics standardizes schema and collection to ensure consistent insights and traceability.

Core Features & Use Cases

Metrics schema and collection procedure for pipeline completion phase, including duration, phases completed, outcomes, and iterations.
Validation and storage rules to enable reliable post-run analytics and auditable dashboards.
Use Case: After a run, feed metrics into dashboards to monitor throughput, quality, and trends across projects.

Quick Start

Run a metrics collection pass after pipeline completion to persist results to docs/plans/{task-key}/metrics.yaml.

Frequently Asked Questions about core-metrics

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

FAQPage Schema

How do I capture pipeline completion metrics for post-run analytics?▼

Capture pipeline completion metrics by running a collection pass after job execution to persist durations, phases, and outcomes into a standardized metrics.yaml file. This enables reliable post-run analytics and auditable dashboards.

What schema does pipeline metrics collection use for validation?▼

Pipeline metrics collection uses a defined metrics schema with built-in validation rules to standardize duration, phases completed, outcomes, and iterations. This ensures consistent insights and traceability across all task runs.

How do I store pipeline metrics to YAML for dashboard integration?▼

Store pipeline metrics to YAML by writing the collection output to docs/plans/{task-key}/metrics.yaml. You can also enable optional MCP storage for archival analytics to feed downstream dashboards and summaries.

Can I use pipeline metrics collection across all task runs and iterations?▼

Pipeline metrics collection applies across all task runs, phases, and iterations without dependencies. It captures execution data end-to-end to produce standardized outputs for monitoring throughput and quality trends.

What is the best way to standardize pipeline metrics collection across projects?▼

Standardize pipeline metrics collection by applying a defined schema and validation rules across all runs. This approach eliminates manual data gathering cycles and ensures consistent, auditable post-run analytics across projects.