This record as markdown: /tools/io-github-ruvnet-claude-flow/todo-complete.md
What todo_complete does on Claude Flow
AI agents use todo_complete to create or update resources in Claude Flow, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Claude Flow environment.
Why todo_complete is rated Medium
This tool performs a reversible state change to a task object (marking complete). It does not delete data, execute arbitrary operations, or have financial impact. The scope is limited to a single task's status field. Severity is low because the blast radius of accidental misuse is minimal—tasks can be unmarked or corrected without loss of data or system integrity.
From the tool's definition Tool name and description: 'Mark a task as complete' — modifies task state by changing its completion status.
Attacks that exploit this kind of access
The rule that runs todo_complete 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 todo_complete, this is the rule to start with:
todo_complete 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 Claude Flow, apply this rule, and every todo_complete call is checked against it from then on.
Questions about todo_complete
Mark a task as complete. It is categorised as a Write tool in the Claude Flow MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Claude Flow MCP server in PolicyLayer and add a rule for todo_complete: 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.
todo_complete 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 todo_complete 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 todo_complete. 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.
todo_complete 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.
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