flowforge
Health Uyari
- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 5 GitHub stars
Code Basarisiz
- exec() — Shell command execution in src/db.ts
- process.env — Environment variable access in src/index.ts
- fs module — File system access in src/index.ts
Permissions Gecti
- Permissions — No dangerous permissions requested
This tool is an enforced workflow engine for AI agents that uses a YAML-driven state machine to ensure processes follow predefined steps without skipping ahead.
Security Assessment
The overall risk is Medium. The primary concern is a critical failure flagged in the code: it explicitly executes shell commands (`src/db.ts`). While no dangerous permissions are requested and there are no hardcoded secrets, the tool reads environment variables and accesses the file system (`src/index.ts`). The inclusion of shell execution means that if an attacker can manipulate a workflow YAML file or an agent's prompt, there is a potential risk of arbitrary command injection.
Quality Assessment
The project is actively maintained, with its most recent push occurring today. It uses the highly permissive MIT license and includes clear documentation to help developers get started quickly. However, the tool suffers from extremely low community visibility, currently boasting only 5 GitHub stars. Because of this small footprint, the codebase has likely not undergone widespread peer review or rigorous security auditing by the open-source community.
Verdict
Use with caution due to the presence of shell command execution alongside low community oversight.
Enforced workflow engine — state machine + gates that block progression until conditions are met
FlowForge
Enforced workflow engine for AI agents — YAML-defined, CLI-driven state machine that prevents agents from skipping steps.
Install
npm install -g @kagura-agent/flowforge
Quick Start
1. Create a workflow YAML
name: my-workflow
description: Example workflow
start: plan
nodes:
plan:
task: Plan the implementation
next: execute
execute:
task: Execute the plan
next: review
review:
task: Review the results
terminal: true
Save this as workflows/my-workflow.yaml (FlowForge auto-discovers workflows from the workflows/ directory).
2. Run the workflow
# Workflows are auto-loaded from workflows/ directory
flowforge list
# Start an instance
flowforge start my-workflow
# Check current status
flowforge status
# Complete current node and advance
flowforge next
# View execution history
flowforge log
Workflow Auto-Loading
FlowForge automatically discovers and loads workflows from:
./workflows/in your current directory~/.flowforge/workflows/in your home directory
Simply drop .yaml or .yml files into these directories and they're immediately available. No need to manually run flowforge define.
YAML Format Reference
Node Types
Linear node (moves to single next node):
nodes:
step1:
task: Do something
next: step2
Branching node (multiple possible paths):
nodes:
check:
task: Evaluate condition
branches:
- condition: success
next: continue
- condition: failure
next: retry
Terminal node (end of workflow):
nodes:
done:
task: Finalize and report
terminal: true
Node Fields
task(required): Natural language description of what to do at this nodenext(optional): Name of next node for linear flowbranches(optional): Array of condition-based paths for branchingterminal(optional): Set totrueto mark as end node
CLI Commands
| Command | Description |
|---|---|
flowforge define <yaml> |
Register or update a workflow |
flowforge start <workflow> |
Start new workflow instance |
flowforge status |
Show current node, task, and branches |
flowforge next [--branch N] |
Complete current node and advance |
flowforge log |
View execution history |
flowforge list |
List all defined workflows |
flowforge active |
List active workflow instances |
flowforge reset |
Reset current instance to start |
flowforge run <workflow> |
Start (or resume) workflow and output next action as JSON |
flowforge advance |
Advance workflow with result and output next action as JSON |
Example Workflow
name: code-contribution
description: Generic open source contribution workflow
start: study
nodes:
study:
task: |
Read project structure, contribution guidelines, and identify
the issue or feature to work on
next: implement
implement:
task: Write code changes according to project patterns
next: test
test:
task: Run tests and verify implementation works
branches:
- condition: tests pass
next: submit
- condition: tests fail
next: implement
submit:
task: Create pull request with clear description
next: verify
verify:
task: Monitor PR feedback and address review comments
terminal: true
Save as contribution.yaml, then:
flowforge define contribution.yaml
flowforge start code-contribution
How It Works
FlowForge enforces step-by-step execution:
- Define workflows as YAML (nodes + transitions)
- Start an instance of a workflow
- Execute the task at current node
- Advance with
flowforge next(or--branch Nfor branching nodes) - Repeat until terminal node
State persists in SQLite database at ~/.flowforge/. Workflows can be paused and resumed across sessions.
Use Cases
- AI agent workflows: Prevent agents from skipping critical steps (e.g., always run tests before submitting)
- Structured processes: Codify learning, contribution, or review workflows
- State machines: Implement branching logic with conditions and history tracking
License
MIT
Star History
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