cost-optimization

SkillDev tools

Cost optimization skill. Review SmartCMP FinOps recommendations or analyze one cloud, software, hardware, virtualized, VM, or database resource for platform-confirmed and LLM-inferred savings opportunities. Use active policy evidence, bounded resource cost facts, risk assessment, and conservative saving estimates; remediate only existing findings through native day2 repair and track remediation state.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the cost-optimization skill

About this capability

A comprehensive knowledge management system for Solutions Architects using AI

What this skill tells your AI

The instructions your AI receives, as published by davidroliverba/architectkb in .claude/skills/cost-optimization/SKILL.md and read by ahel’s review.

Use this skill to work through cost optimization recommendations from discovery to remediation tracking.

Handlers and helpers

scripts/adapter.py contains all five Tool handlers for listing, analysis, execution, and tracking. scripts/_cost_object_actions.py remains separate because the embedded assistant Context resolver calls it to build resource actions; it is not a one-command forwarding script.

Workflow

Choose the entry path that matches the user's object:

  1. Analyze an existing recommendation:
    • Call smartcmp_list_cost_recommendations
    • Optionally request related policy counts
    • Call smartcmp_analyze_cost_recommendation
    • Let SmartCMP Provider resolve the related resourceId
    • Merge normalized resource type + properties into the analysis facts
    • Returns multi-dimensional recommendations (P0/P1/P2 priority)
    • Includes risk assessment and best practice guidance
    • Shows saving contribution, policy history, and resource operational context
  2. Analyze a resource directly:
    • Call smartcmp_analyze_resource_cost with an exact visible name or recent list # selection
    • Read resource facts, enabled applicable policy configurations, latest resource executions, and active violations without triggering policy execution
    • Use the returned analysisContract to keep platform facts separate from llm_potential
    • Read references/RESOURCE_ANALYSIS.md for VM, AWS RDS, and generic resource reasoning rules
  3. Call smartcmp_execute_cost_optimization for native day2 repair only after the user explicitly requests it
  4. Track remediation state with smartcmp_track_cost_optimization

Analysis Output Enhancement

smartcmp_analyze_cost_recommendation provides:

  • P0 Primary Action: Provider recommendation (remediate / configure_platform_policy / manual_review)
  • P1 Risk Assessment: Risk level (high/medium/low) with specific warnings
  • P1 Configuration Guide: When fixType is missing, explains how to configure day2 repair
  • P1 Saving Priority: Contribution percentage to global optimizable amount
  • P2 Policy History: Compliance rate trend and violation recurrence count
  • Resource Context: Resource type, component type, status, OS, and normalized datasource facts

Safety Boundary

The skill only performs platform-native remediation through:

  • POST /compliance-policies/violations/day2/fix/{id}

It does not call AWS or Azure APIs directly.

Resource-first analysis is read-only. It must not call:

  • POST /compliance-policies/execute
  • POST /compliance-policies/violations/day2/fix/{id}

Only an existing platform violation may enter the separate remediation flow. An llm_potential result is never executable.

Resource Enrichment

SmartCMP Provider resolves and reads resource evidence whenever a recommendation includes resourceId.

  • Pull resource details before rendering the final analysis output.
  • Merge resource status/type/OS and normalized facts into facts and downstream recommendations.
  • If resource lookup is unavailable, continue with policy/violation analysis as a best-effort degradation path.

Signals

GitHub stars
52
Forks
12
Last commit
Mar 2026
Advanced
Catalog kind
skill
Gateway key
cost-optimization
Source
github.com/davidroliverba/architectkb