How I Automated My Manus AI Workflow (And Saved 62%)

My Manus AI workflow used to be: think of task → write prompt → wait → repeat.

Now it's: think of task → Credit Optimizer handles the rest.

What Changed

1. Automatic model selection: Each prompt gets analyzed for complexity. Simple tasks go to Standard (70% cheaper), complex ones go to Max.

2. Context hygiene: Unnecessary context is stripped before execution. Saves 10-30% on tokens.

3. Task decomposition: Mixed prompts ("do X AND Y") get split into sub-tasks, each routed optimally.

4. Smart Testing: Uncertain tasks run on Standard first. Only escalate if quality check fails.

Results After 30 Days

• 62% average savings
• 99.2% quality maintained
• Zero manual intervention needed

How It Works

The Credit Optimizer skill installs as a Manus AI skill. Once active, it intercepts every prompt and:

1. Classifies complexity using First Principles analysis
2. Checks for mixed tasks and decomposes if needed
3. Applies context hygiene rules
4. Routes to the optimal model
5. Validates output quality

No configuration needed. It just works.

The Numbers

Metric	Before	After
Avg cost/task	$0.85	$0.32
Monthly spend	$170	$64
Quality score	99.5%	99.2%
Manual routing	100%	0%

Try It

The skill is free and open source:

• Landing Page — full documentation
• GitHub — source code
• Savings Calculator — estimate your savings

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What repetitive AI workflow tasks have you automated? Share in the comments!