workflow_delete
Delete a 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-delete.md
What workflow_delete does on Ruflo
AI agents call workflow_delete to permanently remove resources in Ruflo, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Why workflow_delete is rated Critical
This tool permanently removes workflow data that cannot be recovered. The workflow contains non-trivial state including dependency graphs, retry policies, pause/resume state, and step-output bindings. Deletion is irreversible and would result in loss of orchestration logic and execution history.
From the tool's definition Tool name is 'workflow_delete' and description explicitly states 'Delete a workflow'. The verb 'delete' combined with the action of removing a workflow (a persistent, structured collection of steps with dependencies, retry policies, and state) indicates…
Attacks that exploit this kind of access
The rule that runs workflow_delete 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_delete, this is the rule to start with:
workflow_delete is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Ruflo, apply this rule, and every workflow_delete call is checked against it from then on.
Questions about workflow_delete
Delete a 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 Destructive tool in the Ruflo MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Ruflo MCP server in PolicyLayer and add a rule for workflow_delete: 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_delete is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the workflow_delete 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_delete. 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_delete 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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