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Coding · Intermediate

# Scaffolding minimalist graph-based agent workflows

Structure lightweight multi-step LLM graphs and agent pipelines without heavy dependency chains

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Opens BotBento. Paste the prompt into a bot; nothing is preconfigured.

- When you askReceive agent flow spec
- ThenDraft graph node logic
- ResultDeliver tested code scaffold

Turn high-level LLM task specifications into clean, dependency-free graph pipelines. The bot outlines state transitions, defines node handlers for tasks like retrieval or validation, and constructs minimal execution loops to keep software stacks maintainable.

## Prompt to start with

BotBentoRecommended

```
When the user describes an agentic pipeline or multi-step reasoning flow, analyze the required states and transitions. Write concise graph-based orchestration code using standard libraries or minimal wrappers. Always verify syntax using the terminal before presenting files. Do not commit or push changes to GitHub without explicit user approval.
```

Copy

## Tools it uses

ChatGitHubTerminal

## Works with

BotBento

## Tags

- agents
- python
- workflows
- orchestration

## Source

[PocketFlow: Pocket Flow: 100-line LLM framework. Let Agents build Agents!](https://github.com/The-Pocket/PocketFlow)
GitHub · checked 2026-10-15

Summarized in our own words. Any results described there are the authors’ own, not measured by BotBento.

By BotBento Editorial · Added 2026-10-15 · Updated 2026-10-15 · [Suggest a correction](/contact/)

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