تشغيل أي مهارة في Manus بنقرة واحدة

ابدأ الآن

cost-optimize

النجوم٠

التفرعات٠

آخر تحديث٢٠ مايو ٢٠٢٦ في ١١:١٢

Analyze token usage patterns and recommend cost optimizations with estimated savings

التثبيت

التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.

تشغيل في Manus

المصدر

jpoindexter

jpoindexter/theft-kit

فتح مستودع GitHub عرض مستودعات المنشئ

تنزيل

تشغيل في Manus

المهن ذات الصلةSOC

استنادا إلى تصنيف SOC المهني

مطوّرو البرمجياتمهن الحاسوب والرياضيات·SOC 15-1252

SKILL.md

readonly

name	cost-optimize
description	Analyze token usage patterns and recommend cost optimizations with estimated savings
argument-hint
allowed-tools	mcp__claude-flow__agentdb_hierarchical-recall mcp__claude-flow__agentdb_pattern-search mcp__claude-flow__agentdb_pattern-store mcp__claude-flow__agentdb_semantic-route Bash

Cost Optimize

Analyze recent token usage across agents and models, identify waste, and recommend specific optimizations with estimated dollar savings.

When to use

When costs are higher than expected or you want to proactively reduce spending. Analyzes model selection efficiency, cache utilization, agent redundancy, and prompt efficiency.

Steps

Load usage data -- call mcp__claude-flow__agentdb_hierarchical-recall to fetch recent token usage records from cost-tracking namespace (last 7 days)
Analyze model fit -- for each agent, assess whether the model tier matches task complexity:
- Agents doing simple tasks (formatting, linting) on Sonnet/Opus -> suggest Haiku or Agent Booster
- Agents doing complex tasks (architecture, security) on Haiku -> flag quality risk
Check cache rates -- compute cache hit rate per agent; if below 60%, recommend enabling or improving prompt caching (90% cost reduction on cache reads)
Detect redundancy -- look for multiple agents performing overlapping tasks, or agents being spawned for work that could be batched
Estimate savings -- for each recommendation, calculate: current cost, projected cost after optimization, dollar savings, percentage reduction
Search patterns -- call mcp__claude-flow__agentdb_pattern-search for previously successful optimizations
Store recommendations -- call mcp__claude-flow__agentdb_pattern-store to record optimization recommendations in cost-patterns namespace
Report -- display: ranked recommendations with savings estimate, total potential savings, implementation priority (quick wins first)

CLI alternative

npx @claude-flow/cli@latest memory search --query "cost optimization strategies" --namespace cost-patterns

المزيد من هذا المستودع

نفس المستودع

managing-context-window

jpoindexter/theft-kit

Use when a conversation is getting long, drifting, juggling multiple tasks, re-pasting the same files, or showing stale/confused context — and at the start of any new task. Triggers: long thread, context bloat, topic switch, repeated file uploads, 'why is it forgetting', degraded answers, finished one task and starting another.

2026-06-010

first-principles-deconstructor

jpoindexter/theft-kit

Use when a user wants to deconstruct a complex problem, business challenge, product decision, strategy question, career crossroads, or stuck situation by stripping assumptions, identifying first principles, rebuilding options from foundational truths, and choosing one high-leverage action.

2026-05-210

access-control-audit

jpoindexter/theft-kit

Audit role-based access control and permission drift across product surfaces.

2026-05-200

add-package-feature

jpoindexter/theft-kit

Add a new feature to an existing @fabrk/* package following monorepo conventions

2026-05-200

adr-index

jpoindexter/theft-kit

Build or rebuild the ADR index and dependency graph in AgentDB

2026-05-200

agentdb-query

jpoindexter/theft-kit

Query AgentDB with semantic routing, hierarchical recall, causal graphs, and context synthesis

2026-05-200

Cost Optimize

Analyze recent token usage across agents and models, identify waste, and recommend specific optimizations with estimated dollar savings.

When to use

When costs are higher than expected or you want to proactively reduce spending. Analyzes model selection efficiency, cache utilization, agent redundancy, and prompt efficiency.

Steps

Load usage data -- call mcp__claude-flow__agentdb_hierarchical-recall to fetch recent token usage records from cost-tracking namespace (last 7 days)

Analyze model fit -- for each agent, assess whether the model tier matches task complexity:

Agents doing simple tasks (formatting, linting) on Sonnet/Opus -> suggest Haiku or Agent Booster
Agents doing complex tasks (architecture, security) on Haiku -> flag quality risk

Check cache rates -- compute cache hit rate per agent; if below 60%, recommend enabling or improving prompt caching (90% cost reduction on cache reads)

Detect redundancy -- look for multiple agents performing overlapping tasks, or agents being spawned for work that could be batched

Estimate savings -- for each recommendation, calculate: current cost, projected cost after optimization, dollar savings, percentage reduction

Search patterns -- call mcp__claude-flow__agentdb_pattern-search for previously successful optimizations

Store recommendations -- call mcp__claude-flow__agentdb_pattern-store to record optimization recommendations in cost-patterns namespace

Report -- display: ranked recommendations with savings estimate, total potential savings, implementation priority (quick wins first)

CLI alternative

npx @claude-flow/cli@latest memory search --query "cost optimization strategies" --namespace cost-patterns