autopilot_progress
Detailed task progress broken down by source (team-tasks, swarm-tasks, file-checklist). Use when running long-horizon goals that should resume automatically across sessions — Claude Code has no native autonomous-loop scheduler. Pair with autopilot_enable + a goal description, then let cron fires ...
This record as markdown: /tools/ruflo/autopilot-progress.md
What autopilot_progress does on Ruflo
AI agents call autopilot_progress to retrieve information from Ruflo without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why autopilot_progress is rated Low
autopilot_progress is explicitly a progress-reporting tool that provides visibility into task state. While it sits within an agent orchestration system, its function is passive observation and reporting (Read). It does not create, modify, delete, or trigger execution of tasks — those are handled by sibling tools like agent_spawn, agent_terminate, and autopilot_enable.
From the tool's definition Tool retrieves 'detailed task progress broken down by source' — it queries and reports status information without modifying, deleting, or executing operations. No side effects described.
Attacks that exploit this kind of access
The rule that runs autopilot_progress 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 autopilot_progress, this is the rule to start with:
autopilot_progress is read-only, so it stays allowed. 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 autopilot_progress call is checked against it from then on.
Questions about autopilot_progress
Detailed task progress broken down by source (team-tasks, swarm-tasks, file-checklist). Use when running long-horizon goals that should resume automatically across sessions — Claude Code has no native autonomous-loop scheduler. Pair with autopilot_enable + a goal description, then let cron fires advance the work. For interactive single-task sessions, native Task is fine. It is categorised as a Read tool in the Ruflo MCP Server, which means it retrieves data without modifying state.
Register the Ruflo MCP server in PolicyLayer and add a rule for autopilot_progress: 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.
autopilot_progress is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the autopilot_progress 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 autopilot_progress. 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.
autopilot_progress 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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