task_update
Update task status or progress Use when native TodoWrite is wrong because you need cross-session task persistence, agent assignment, dependency tracking, or completion analytics in the .swarm/memory.db. For in-session checklists native TodoWrite is simpler and faster.
This record as markdown: /tools/ruflo/task-update.md
What task_update does on Ruflo
AI agents use task_update 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 task_update is rated Medium
This tool creates or modifies task metadata and progress tracking in a persistent database. While the modifications are reversible (tasks can be re-updated), the tool directly alters state in a shared multi-agent coordination system. The mention of 'agent assignment' and 'dependency tracking' suggests the updates could affect workflow execution across agents, making it Write rather than Read.
From the tool's definition Tool description explicitly states 'Update task status or progress' and mentions writing to '.swarm/memory.db'. The tool modifies task records including status, progress, agent assignment, and completion analytics—all reversible write operations.
Attacks that exploit this kind of access
The rule that runs task_update 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 task_update, this is the rule to start with:
task_update 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 task_update call is checked against it from then on.
Questions about task_update
Update task status or progress Use when native TodoWrite is wrong because you need cross-session task persistence, agent assignment, dependency tracking, or completion analytics in the .swarm/memory.db. For in-session checklists native TodoWrite is simpler and faster. 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 task_update: 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.
task_update 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 task_update 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 task_update. 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.
task_update 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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