workflow_create
Create a new workflow Use when native TodoWrite + sequential Bash is wrong because the work has a real dependency graph that needs persistence, retry policy, pause/resume, and step-output binding across LLM-driven steps. For a single linear todo list, native TodoWrite is fine.
This record as markdown: /tools/ruflo/workflow-create.md
What workflow_create does on Ruflo
AI agents use workflow_create to create or update resources in Ruflo, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ruflo environment.
Why workflow_create is rated Medium
The tool creates and persists new workflow objects with execution logic and state management. While reversible (workflows can be deleted), the creation of autonomous multi-step workflows that bind LLM outputs and execute with retry/resume capabilities poses a medium-to-high risk if an agent misuses it to instantiate unintended orchestration tasks, resource chains, or trigger unwanted multi-step agent behaviors…
From the tool's definition Tool name is 'workflow_create' and description states 'Create a new workflow' — a create operation that produces persistent artifacts with 'dependency graph', 'retry policy', 'pause/resume', and 'step-output binding.' This creates reversible state in the…
Attacks that exploit this kind of access
The rule that runs workflow_create safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ruflo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For workflow_create, this is the rule to start with:
workflow_create stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Ruflo, apply this rule, and every workflow_create call is checked against it from then on.
Questions about workflow_create
Create a new workflow Use when native TodoWrite + sequential Bash is wrong because the work has a real dependency graph that needs persistence, retry policy, pause/resume, and step-output binding across LLM-driven steps. For a single linear todo list, native TodoWrite is fine. It is categorised as a Write tool in the Ruflo MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ruflo MCP server in PolicyLayer and add a rule for workflow_create: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ruflo. Nothing to install.
workflow_create is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the workflow_create rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for workflow_create. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
workflow_create is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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