Why SuperAGI Developers Need AgentGenome
SuperAGI agents use tools to accomplish goals. AgentGenome profiles tool selection, usage patterns, and effectiveness—so your agents use tools consistently across any LLM.
Agent Toolkits Lack Effectiveness Data
Your SuperAGI agent has 20 tools. Which ones work? Which are underused? Without profiling, tool effectiveness is invisible.
Tool Selection Is Unpredictable
When does your agent choose web search vs. code execution? Without behavioral baselines, tool selection seems random.
Tool Patterns Are LLM-Specific
Tool selection on GPT-4 differs from Claude. Can you maintain tool usage quality across providers?
Adding New Tools Might Break Old Patterns
New tools can confuse existing tool selection. AgentGenome tracks how tool changes affect agent behavior.
"Sound familiar?"
AgentGenome Solves Every Problem
Add 3 lines of code. Capture your agent's behavioral DNA. Deploy anywhere.
from superagi import SuperAGI
from agentgenome import profile_tools
agent = SuperAGI(model="gpt-4", tools=["web_search", "code_executor", "file_writer"])
@profile_tools(genome_id="tool-agent")
def accomplish(goal: str):
return agent.execute(goal)
# Tool selection and usage patterns capturedWhat You Get
- Behavioral profiling without code changes
- 35% average token savings
- Real-time drift detection
- Substrate-independent genome export
- Multi-provider deployment ready
Profile Once. Deploy Anywhere.
Tool profiles port anywhere. Capture how your agent selects and uses tools—deploy those patterns on any LLM without losing tool effectiveness.
Your SuperAGI Agents Deserve Freedom
You've invested months optimizing SuperAGI prompts. What happens when costs rise, performance drops, or a better model launches?
✗Without AgentGenome
- •Start over. Rebuild every prompt from scratch.
- •Lose months of behavioral optimization.
- •4-6 weeks of engineering per migration.
- •$47K+ average migration cost.
- •40%+ behavioral drift during migration.
With AgentGenome
- ✓Export your behavioral genome in one click.
- ✓Import to AutoGPT, BabyAGI, AgentGPT, or any provider.
- ✓Keep your optimizations. Zero rework.
- ✓95%+ behavioral consistency guaranteed.
- ✓Hours, not weeks. Included in Pro tier.
# Export tool usage genome
from agentgenome import genome
# Capture tool selection patterns
genome.export('tool-agent.genome')
# Deploy on Claude with same tool patterns
genome.import_to('tool-agent.genome', provider='anthropic')
# Same tool effectiveness, new substrateDeploy your SuperAGI genome on any supported provider:
Profile once. Deploy anywhere. Never locked in.
Build SuperAGI applications Once.
Deploy on Any LLM.
Tool profiles port anywhere. Capture how your agent selects and uses tools—deploy those patterns on any LLM without losing tool effectiveness.
Your Agent Genome
Behavioral DNA captured in universal format
Profile Your SuperAGI applications
Add 3 lines of code. Capture behavioral DNA automatically.
from superagi import SuperAGI
from agentgenome import profile_tools
agent = SuperAGI(model="gpt-4", tools=["web_search", "code_executor", "file_writer"])
@profile_tools(genome_id="tool-agent")
def accomplish(goal: str):
return agent.execute(goal)
# Tool selection and usage patterns capturedYour applications become substrate-independent
Profile today, deploy on any LLM tomorrow. Your optimizations travel with you.
Real Results with AgentGenome
How ToolsFirst Made Tool Selection Portable
The Challenge
ToolsFirst's multi-tool agent had learned optimal tool selection on GPT-4 over 6 months. When exploring Claude for cost savings, they needed to preserve tool usage patterns.
The Solution
AgentGenome profiled tool selection patterns—which tools for which tasks, tool combinations, and fallback behaviors. The tool genome was deployed on Claude.
"Six months of tool learning shouldn't be locked to one provider. Now our tool wisdom travels with us."
— Mark Stevens, CTO, ToolsFirst
Without vs With AgentGenome
| Aspect | Without AgentGenome | With AgentGenome |
|---|---|---|
| Debugging Time | 4+ hours per incident | 52 minutes average (-78%) |
| Token Efficiency | Unknown waste | 35% average savings |
| Behavioral Visibility | Black box | Full trait analysis |
| Drift Detection | Discover in production | Catch before deployment |
| Agent Portability | 🔒 Locked to SuperAGI | 🔓 Deploy on any LLM |
| Migration Time | 4-6 weeks per provider | Hours with genome export |
| Migration Cost | $47K+ engineering | Included in Pro tier |
| Multi-Provider Strategy | Rebuild for each | One genome, all providers |
| Future-Proofing | Start over when models change | Take your genome with you |
| Vendor Negotiation | No leverage (locked in) | Full leverage (can leave) |
The Cost of Waiting
💸 Financial Lock-In
- SuperAGI pricing has increased multiple times since launch
- Without portable profiles, you pay whatever they charge
- Migration estimate without AgentGenome: $47K and 8 weeks
⚠️ Strategic Lock-In
- Better alternatives might exist—but can you actually switch?
- Your competitors are profiling for portability right now
- When you need to migrate, will you be ready?
🔒 The Vendor Lock-In Tax
- 4-6 weeks of engineering to migrate unprofiled agents
- 40%+ behavioral drift during manual migration
- Zero leverage in pricing negotiations
📉 Competitive Disadvantage
- Competitors with portable profiles ship 80% faster
- They negotiate contracts with leverage—you don't
- They test new models in hours; you take months
"Every day without profiling locks you deeper into SuperAGI."
When SuperAGI raises prices or a better model launches, will you be ready to leave?
What You'll Achieve with AgentGenome
Real metrics from SuperAGI users who profiled their agents
Before AgentGenome
- • Debugging: 4+ hours per incident
- • Migration: 4-6 weeks per provider
- • Token waste: Unknown
- • Drift detection: In production
- • Vendor leverage: None
After AgentGenome
- • Debugging: 52 minutes average
- • Migration: Hours with genome export
- • Token savings: 35% average
- • Drift detection: Before deployment
- • Vendor leverage: Full (can leave anytime)
Already Locked Into SuperAGI?
Here's how to escape with your behavioral DNA intact
Profile Your Current Agent
Add 3 lines of code to capture your SuperAGI agent's behavioral DNA. No changes to your existing logic.
Export Your Genome
One command exports your substrate-independent genome. It works on any LLM provider, not just SuperAGI.
Deploy Anywhere
Import your genome to Claude, Gemini, Llama, or any provider. 95%+ behavioral consistency, zero rework.
Zero-Downtime Migration Promise
AgentGenome's migration assistant guides you through the process. Profile your current agent while it's running, export the genome, and deploy to a new provider—all without touching your production system until you're ready.
Start Free. Unlock Portability with Pro.
Most SuperAGI developers choose Pro for multi-provider genome sync. Start free and upgrade when you need portability.
| Portability Features | Free | Pro | Enterprise |
|---|---|---|---|
| Genome Export | JSON only | JSON + YAML | All formats |
| Multi-Provider Sync | — | ✓ | ✓ + Custom |
| Migration Assistant | — | ✓ | ✓ + SLA |
| Custom Substrate Adapters | — | — | ✓ |
Frequently Asked Questions
Everything you need to know about AgentGenome for SuperAGI