set_status
Move a task between Todo / In Progress / Review / Done. Review sits between In Progress and Done when requireReview is on; approve:true overrides the gate. When moving to Done you can also record structured completion metadata (model, tokens, additions, deletions) — these are written to the work ...
This record as markdown: /tools/ai-featureboard-featureboard/set-status.md
What set_status does on FeatureBoard
AI agents use set_status to create or update resources in FeatureBoard, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your FeatureBoard environment.
Why set_status is rated Medium
set_status modifies task state and creates/writes completion metadata to logs, which are reversible operations characteristic of Write category. While it touches git workflows and metrics, the core function is updating task status and recording work log entries.
From the tool's definition Tool description states it moves tasks "between Todo / In Progress / Review / Done" and can "record structured completion metadata" that is "written to the work log". These are state modifications and data creation operations.
Attacks that exploit this kind of access
The rule that runs set_status safely
PolicyLayer is an MCP gateway: it sits between your AI agents and FeatureBoard, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For set_status, this is the rule to start with:
set_status 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 FeatureBoard, apply this rule, and every set_status call is checked against it from then on.
Questions about set_status
Move a task between Todo / In Progress / Review / Done. Review sits between In Progress and Done when requireReview is on; approve:true overrides the gate. When moving to Done you can also record structured completion metadata (model, tokens, additions, deletions) — these are written to the work log and roll up into velocity/metrics. For graduated projects, moving to Done also refreshes the pad snapshot in <codeRepo>/.featureboard/ (best-effort; a mirror failure never blocks the status change). If git is enabled for the project and Done is reached with no commit referencing the ticket (recorded via commit_feature, or found via git log --grep), the response carries uncommitted:true + a commitReminder — or, when requireCommitOnDone is on, the move is refused outright (approve:true overrides). It is categorised as a Write tool in the FeatureBoard MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the FeatureBoard MCP server in PolicyLayer and add a rule for set_status: 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 FeatureBoard. Nothing to install.
set_status 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 set_status 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 set_status. 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.
set_status is provided by the FeatureBoard MCP server (https://github.com/valentil/featureboard-mcp/releases/download/v0.7/featureboard.plugin). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on FeatureBoard, and thousands of servers like it.
This server
Across the catalogue