dora-report

name	dora-report
description	Generate monthly DORA and agentic metrics reports. Use this skill when the user asks for a DORA report, monthly metrics, or a monthly audit. Not for readme-best-practices.
category	devops
version	0.2.10
template_version	0.3
license	MIT

DORA Report

Generate and maintain DORA (DevOps Research and Assessment) metrics and agentic performance metrics to track project velocity, stability, and agent efficiency.

When to Use

Activate when:

• Monthly reporting is required (e.g., at the end of a calendar month).
• The user requests a performance audit or "DORA report".
• Analyzing the impact of new tools or workflows on delivery speed and quality.

Instructions

1. Calculate DORA Metrics:

   • Deployment Frequency: How often code is successfully released to production (or merged to main in this template context).
   • Lead Time for Changes: The amount of time it takes a commit to get into production.
   • Change Failure Rate: The percentage of deployments causing a failure in production (e.g., requiring a hotfix or revert).
   • Time to Restore Service: How long it takes to recover from a failure in production.

2. Calculate Agentic Metrics:

   • Tasks Completed: Total number of GOAP goals or atomic tasks finalized.
   • Skill Invocations: Frequency and distribution of skill usage.
   • Token Usage Trends: Efficiency of context usage over time.
   • Self-Fix Success Rate: Ratio of auto-fixed CI failures vs. those requiring human intervention.

3. Generate Report:

   • Create or append to agents-docs/dora-reports/YYYY-MM.md.
   • Use standardized tables and charts (Mermaid where appropriate).
   • Compare current metrics against the previous month's baseline.

4. Identify Bottlenecks:

   • Based on metrics, suggest one "Innovation Opportunity" using TRIZ principles to improve a lagging metric.

Instructions

1. Run the automation script: python3 scripts/generate_report.py
2. Verify the output in agents-docs/dora-reports/YYYY-MM.md.
3. Add any qualitative analysis or TRIZ-based innovation opportunities to the generated file.

See Also

• learn — Extract learnings into AGENTS.md
• readme-best-practices — README and documentation best practices

Rationalizations

Rationalization	Reality
"Metrics are for managers, not agents"	Metrics provide the feedback loop for agentic self-improvement and workflow optimization.
"It's too hard to track lead time manually"	Agents can analyze git history and PR timestamps to automate this calculation.
"A monthly report is too frequent for a small repo"	Regular snapshots prevent technical debt from accumulating unnoticed.

Red Flags

• Reporting "zero" for failures without verifying revert history or hotfix commits.
• Ignoring "agentic overhead" (e.g., extremely high token usage for simple tasks).
• Metrics that lack a time-bound context (e.g., "total tasks" instead of "tasks per week").

References

• agents-docs/WORKFLOW.md - Standard delivery process to measure against.
• scripts/analyze-codebase.sh - Source for some raw performance data.

Voice & Context

• Default: professional + blog
• Reference: voice-profiles skill for definitions and auto-detection.