TikTok Shop Growth Strategist with OpenAI Agents SDK and E2B
Capitalizing on TikTok Shop's massive Q1 growth, this challenge requires building an autonomous marketing and supply chain agent team. Using the OpenAI Agents SDK and GPT-5.4 Pro, you will create agents capable of analyzing sales volume data and predicting trend cycles. The system must leverage E2B as a secure sandboxed environment to execute complex Python scripts for market analysis. You will use Speakeasy to generate clean SDKs for custom e-commerce APIs and OpenRouter to route specific reasoning sub-tasks to the most cost-effective models. The final implementation will include All Hands AI to provide a collaborative interface where human managers can approve agent-proposed stock reorders.
What you are building
The core problem, expected build, and operating context for this challenge.
Build an e-commerce intelligence system using OpenAI Agents SDK, GPT-5.4 Pro, and E2B for sandboxed data analysis.
How work is evaluated
The evaluation checks the agent's ability to generate valid forecasting code and execute it in E2B to produce a growth report.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Code Validity
Agent-generated code must run without errors in E2B
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Forecast Precision
Variance between agent prediction and historical growth trends • target: 5 • range: 0-100
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement the OpenAI Agents SDK to create task-oriented agents with function-calling capabilities
Master E2B Code Interpreter for running autonomous data science scripts without compromising host security
Use Speakeasy to create standardized SDKs for legacy TikTok Shop and warehouse management APIs
Design model routing logic with OpenRouter to switch between GPT-5.4 Pro for strategy and GPT-5.4-mini for simple reporting
Build a collaborative agent dashboard with All Hands AI for real-time task visibility
Deploy complex long-term memory patterns for agents to remember seasonal TikTok trends
Reference links and supporting material
Sample data for 1 tasks
Challenge setup
The evaluation checks the agent's ability to generate valid forecasting code and execute it in E2B to produce a growth report.
Challenge input
CSV of sales data for TikTok Shop
E2B
Cloud sandboxes for AI agents.
OpenAI
OpenAI AI model provider
OpenRouter
Unified model API and router.
Evaluated output
Percentage growth figure and prediction graph
- Agent-generated code must run without errors in E2B
- Variance between agent prediction and historical growth trends • target: 5 • range: 0-100
- Forecast Precision target: 5
- 1 public reference case
- Python execution harness
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- E2B · Required
- OpenAI · Optional
- OpenRouter · Optional
Evaluation contract
- Code Validity · Weight 1
- Forecast Precision · Weight 1
Metrics
- Forecast Precision · Target 5
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: CSV of sales data for TikTok Shop
Output: Percentage growth figure and prediction graph
Execution harness: Python
Recipe freeze marker
No recipe freeze time is recorded.