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Finops Compare

  • 54 installs
  • 49 repo stars
  • Updated August 4, 2026
  • laurigates/claude-plugins

Helps with ai & agent building tasks.

About

finops-compare is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • finops-compare
  • AI & Agent Building
  • AI-coding skill

Finops Compare by the numbers

  • 54 all-time installs (skills.sh)
  • Ranked #6,946 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/laurigates/claude-plugins --skill finops-compare

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Listed on Skillselion
Installs54
repo stars49
Last updatedAugust 4, 2026
Repositorylaurigates/claude-plugins

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

/finops:compare

Compare GitHub Actions FinOps metrics across multiple repositories - cache usage, workflow frequency, failure rates, and efficiency.

When to Use

ScenarioUse this skillAlternative
Compare CI metrics across org repos/finops:compare-
Identify worst-performing repos in org/finops:compare-
Org-wide cache or failure audit/finops:compare-
Deep-dive into a single repo's caches/finops:cachesUse caches for single-repo detail
Deep-dive into a single repo's workflows/finops:workflowsUse workflows for per-repo analysis
Quick summary of current repo only/finops:overviewUse overview for single-repo snapshot

Parameters

ParameterDescriptionDefault
orgGitHub organization name (required)-
repos...Space-separated list of repo namesAll org repos
--limit NLimit auto-discovery to N repos30

Usage Examples

# Compare specific repos
/finops:compare myorg repo1 repo2 repo3

# Compare all repos in org (up to 30)
/finops:compare myorg

# Compare more repos
/finops:compare myorg --limit 50

Execution

bash "${SKILL_DIR}/scripts/compare-repos.sh" $ARGS

Output Format

=== FinOps Comparison: myorg ===

Discovering repos (limit: 30)...
Found 25 repos

=== Cache Usage ===
Repository                               Caches    Size (MB)
----------                               ------    ---------
frontend-app                                 45         2340
backend-api                                  32         1850
shared-libs                                  18          420
...

=== Workflow Activity (last 30 days) ===
Repository                                 Runs  Success   Failed  Skip Rate
----------                                 ----  -------   ------  ---------
frontend-app                                156      140       10         3%
backend-api                                  89       85        2         2%
...

=== Failure Rates (top 15) ===
Repository                                Total   Failed       Rate
----------                                -----   ------       ----
legacy-service                               45       12        26%
experimental-repo                            20        5        25%
...

=== Active Workflows ===
Repository                               Workflows
----------                               ---------
frontend-app                                     8
backend-api                                      5
...

=== Summary ===
Total cache usage: 8450MB across 25 repos

Repos exceeding 1GB cache:
  frontend-app: 2340MB
  backend-api: 1850MB

Repos with >20% failure rate:
  legacy-service: 26%
  experimental-repo: 25%

Agentic Optimizations

ContextCommand
List org repos (JSON)gh api "/orgs/{org}/repos?per_page=100&sort=pushed" --jq '.[].full_name'
Cache count per repogh api "/repos/{owner}/{repo}/actions/caches" --jq '.total_count'
Workflow runs (JSON)gh api "/repos/{owner}/{repo}/actions/runs?per_page=100" --jq '.workflow_runs'
Compact multi-repo comparebash "${SKILL_DIR}/scripts/compare-repos.sh" $ARGS

Post-actions

Based on comparison results:

  • High cache repos: Run /finops:caches <repo> for detailed analysis
  • High failure repos: Run /finops:workflows <repo> to investigate
  • High activity repos: Run /finops:waste <repo> to find optimizations
  • Create report: Consider creating a GitHub issue with findings

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