cloud-finops-skills: Cloud FinOps Skill & MCP by OptimNow

by OptimNow · MCP Server · ★ 66

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsai-cost-managementawsazurechargebackclaude-codecloud-cost-optimizationcloud-financial-managementcloud-governancedatabricks

Quick Facts

Stars66
Forks18
LanguagePython
CategoryMCP Server
LicenseCC-BY-SA-4.0
Quality Score63/100
Open Issues1
Last Updated2026-11-07
Created2026-02-25
Platformsaws, claude-code, k8s, mcp, python
Est. Tokens~21k

About cloud-finops-skills

cloud-finops-skills Built by OptimNow. Covers cloud financial management across AWS, Azure, GCP, AI inference costs, GenAI capacity planning, SaaS asset management, and tagging governance - grounded in enterprise delivery experience. Install in 5 seconds [Download the latest release zip](https://github.com/OptimNow/cloud-finops-skills/releases/latest

Compatible Skills

These tools work well together with cloud-finops-skills for enhanced workflows:

  • claude-code-skill-example — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • Halberd — semantic(0.20)+complementary+rare_topics+shared_platform (45%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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