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/io-github-ruvnet-claude-flow/workflow-delete.md
What workflow_delete does on Claude Flow
AI agents call workflow_delete to permanently remove resources in Claude Flow, 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 irreversibly deletes workflow entities and their associated state. Unlike Write tools that modify data reversibly, deletion cannot be undone. The high severity reflects that workflows in an enterprise orchestration system likely represent critical automation pipelines, and deleting one could disrupt dependent processes, lose execution history, and interrupt multi-step operations.
From the tool's definition Tool name is 'workflow_delete' and description states 'Delete a workflow', which explicitly indicates irreversible deletion of persisted workflow data including dependency graphs, retry policies, and step-output bindings.
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 Claude Flow, 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 Claude Flow, 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 Claude Flow MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Claude Flow 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 Claude Flow. 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 Claude Flow MCP server (claude-flow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Claude Flow, and thousands of servers like it.
Across the catalogue