My First Manus - Adding Agent Criteria, Obtaining Best Instructions and Approach, Testing the Guardrails
A few days ago I created a criteria matrix for judging the quality of an illustrated animation (https://exploringallthethings.blogspot.com/2025/03/coherence-matrix-draft.html).
The criteria matrix contains sections for both tradtional and ai/ml metrics broken down into agentic roles in an animation pipleline (Prototyping AI agents is really interesting. More on that on the blog).
Once I had that criteria metric scale that can become a trigger in a function, and the handoff between agents described, I began to translate it into a few different tools.
One is for a test to see what Manus.im can do, since I just got the invite, and wanted to use my free prompts to onboard and simultaneously gauage how it might approach the criteria matrix out of curiosity.
It was late, so I didn't think much about the prompt. But, I did feed it the criteria as a pdf.
Then, I ran my first Manus.
I plan to do a lot more with it, but easily exhaused the free inital credits before getting very far. But, here's a sample of what my first prompt accomplished.
Manus.im Output:
Recommendations for Using Manus.im with Your AI Animation Framework
Specific Recommendations Based on Your Document
Your "Agentic Criteria & Coherence Matrix for AI Animation" document provides an excellent foundation for creating AI animation workflows. Here are specific recommendations for implementing your framework using Manus.im:
1. Implement Your Full Pipeline Simulation
The example prompt you provided on lines 579-597 of your document is an excellent starting point:
```
You are an orchestrator managing a multi-agent AI animation pipeline using the Agentic Criteria & Coherence Matrix. Simulate a sequential creative process across these roles:
1. Storyteller – narrative, tone, symbolism
2. Visual Designer – style, shape language, lighting
3. Character Artist – consistent characters, expressions
4. Animator – motion dynamics, timing, gesture
5. Colorist / Lighting – emotional color and contrast
6. Model Engineer – fidelity, coherence, reroute logic
Each agent:
- Outputs structured content
- Scores its output (1–5)
- Passes handoff notes
- Reruns if score < 3
Begin with the Storyteller. End with an evaluation summary.
```
This prompt structure leverages Manus.im's ability to simulate a full creative AI pipeline within a single structured prompt.
### 2. Enhance with Detailed Evaluation Criteria
Expand your prompt by incorporating the specific evaluation criteria from your Coherence Evaluation Matrix:
```
For each agent, evaluate outputs using these criteria:
Storyteller:
- Staging: Clarity of narrative focus in each scene
- Anticipation: Use of visual cues to foreshadow events
- Timing: Emotional pacing that matches story beats
- Appeal: Characters and visuals that support the story's tone
- Scene Continuity: Logical progression and visual consistency between scenes
- Mood Progression: Emotional tone that evolves meaningfully over time
Visual Designer:
- Color: Palette choices enhance emotion and hierarchy
- Shape Language: Consistent stylization across characters and environments
- Texture / Style: Unified visual style across the sequence
- Lighting: Creates atmosphere and directs attention
- Exaggeration: Visual distortion to enhance clarity or emotion
[Continue with criteria for other roles]
```
### 3. Implement the Agent-to-Agent Workflow
Your "Agent-to-Agent Workflow Flow" table provides valuable guidance on how outputs should move between agents:
```
Define these handoff contents between agents:
From Storyteller to Visual Designer:
- Story beats, tone, symbolism
- Purpose: Establish mood and direction
- Feedback trigger: If misaligned tone is detected
From Visual Designer to Character Artist:
- Style guide, shape rules
- Purpose: Ensure on-model design
- Feedback trigger: If visual identity diverges
[Continue with other handoffs]
```
### 4. Utilize the Three Prompt Levels
Your document defines three levels of prompts (Beginner, Advanced, Multimodal) that can be adapted based on your familiarity with Manus.im:
- **Start with Beginner prompts** as you learn the platform
- **Progress to Advanced prompts** as you become more comfortable
- **Implement Multimodal prompts** when you're ready to combine text, image, and motion inputs
### 5. Create a Custom Scoring System
Implement your 1-5 scoring system with specific thresholds for action:
```
Scoring Key (1–5):
5: Excellent – Fully aligned, high-quality, and coherent output
4: Good – Minor inconsistencies but solid performance overall
3: Adequate – Meets basic requirements; room for improvement
2: Needs Improvement – Gaps in logic, quality, or alignment
1: Poor – Output is incoherent, off-target, or unusable
If any score falls below 3, the Orchestrator should:
1. Identify specific issues using the evaluation criteria
2. Provide targeted feedback to the relevant agent
3. Request a rerun with adjusted parameters
```
## Next Steps for Implementation
1. **Start with a simplified version** of your framework to test Manus.im's capabilities
2. **Gradually add complexity** as you become more familiar with the platform
3. **Document results and refine** your approach based on outputs
4. **Experiment with different prompt structures** to find what works best
5. **Consider integrating external tools** mentioned in your document (e.g., Midjourney, DALL·E 3, Pika, Runway)
## Potential Challenges and Solutions
### Challenge 1: Complexity Management
Your framework is comprehensive and might be challenging to implement in a single prompt.
**Solution**: Break it down into modular components that can be chained together. Start with implementing just 2-3 agent roles, then expand.
### Challenge 2: Evaluation Consistency
Ensuring consistent evaluation across different creative aspects can be difficult.
**Solution**: Create detailed rubrics for each evaluation criterion with specific examples of what constitutes each score level.
### Challenge 3: Tool Integration
Your document mentions various external tools that might need to be integrated.
**Solution**: Start with what Manus.im can do natively, then explore its ability to orchestrate external tools as you become more familiar with the platform.
## Conclusion
Your "Agentic Criteria & Coherence Matrix for AI Animation" provides an excellent framework that aligns well with Manus.im's capabilities. By implementing your framework as structured prompts with clear roles, evaluation criteria, and feedback loops, you can leverage Manus.im to create sophisticated AI animation workflows.
Start with simpler implementations and gradually increase complexity as you become more familiar with the platform. Document your results and continuously refine your approach based on the outputs you receive.
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