highflame-ai/ai-factory/optimize

Claude Code and agent skill by highflame-ai/ai-factory

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API cost & performance scanner — identify expensive operations and optimization opportunities

Install

npx vskill@latest install highflame-ai/ai-factory/optimize

Semi-extensibleMentions customization, but needs skill-specific knowledge. Read the extensible skills standard

SKILL.md

/optimize — API Cost & Performance Scanner

You are scanning this project's API and infrastructure for cost and performance optimization opportunities.

Ethos

!sh .aif/partials/ethos-include.sh 2>/dev/null || sh ~/.claude/skills/partials/ethos-include.sh

Context

  • Architecture: !cat .aif/context/architecture.md 2>/dev/null || echo "No architecture context found"
  • Project overview: !cat .aif/context/project-overview.md 2>/dev/null || echo "No project overview found"

Input

Focus: $ARGUMENTS

Prerequisites

Before proceeding, verify that .aif/context/architecture.md and .aif/context/project-overview.md exist. If any of these files are missing, stop and tell the user: "The .aif/ structure hasn't been initialized. Run /init first to set up the project context."

Instructions

Step 1: Determine Focus
  1. If given a focus area, prioritize that dimension
  2. If no argument, scan all dimensions
  3. Read .aif/context/architecture.md for current caching and optimization patterns
Step 2: Launch Scanner Agents

Launch 3 formal scanner agents in parallel using the Agent tool. Each agent is defined in ~/.claude/agents/ with its full scanning checklist and model selection (sonnet for deep analysis).

  1. api-cost-scanner agent — provide the focus scope and architecture.md for caching context
  2. db-perf-scanner agent — provide the focus scope
  3. latency-scanner agent — provide the focus scope

Each agent returns structured findings with estimated impact, effort, and risk.

Step 3: Build Optimization Report
Cost Summary
ServiceEst. Monthly UsageEst. Monthly CostTop Optimization
Claude SonnetX calls$X...
Claude HaikuX calls$X...
Gemini FlashX calls$X...
SerpAPIX calls$X...
FirestoreX reads/writes$X...
GCSX operations$X...
Performance Hotspots

Rank endpoints by estimated latency, highlighting:

  • Sequential operations that could be parallel
  • Missing caches
  • N+1 query patterns
  • Unnecessary data fetching
Optimization Opportunities

For each opportunity:

  • What: Description of the optimization
  • Impact: Cost savings or latency reduction estimate
  • Effort: Small / Medium / Large
  • Risk: Low / Medium / High (chance of breaking something)
Step 4: Prioritized Recommendations
  1. Rank optimizations by impact/effort ratio
  2. Group into quick wins (small effort, high impact) and strategic improvements
  3. Suggest which items warrant a full AIF requirement (candidates for /spec)

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

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