plan_budget

Map a token budget onto the priority-ordered open queue BEFORE spending it: assigns tickets to days (greedy load-balance),

SERVERFeatureBoard SOURCEhttps://github.com/valentil/featureboard-mcp/releases/download/v0.7/featureboard.plugin

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/ai-featureboard-featureboard/plan-budget.md

WHAT IT DOES

What plan_budget does on FeatureBoard

AI agents use plan_budget 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.

RISK

Why plan_budget is rated Medium

This tool modifies scheduling metadata by assigning tickets to specific days based on token budget constraints. While reversible (assignments can be changed), it creates and updates ticket state, qualifying it as Write rather than Read. The severity is medium because misuse could misallocate work across a project timeline, delaying critical tasks, but the changes are recoverable.

From the tool's definition Tool description states it 'assigns tickets to days', which is a modification of ticket state/scheduling. The name 'plan_budget' and verb 'assigns' indicate data creation/update of task assignments rather than deletion or irreversible changes.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs plan_budget 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 plan_budget, this is the rule to start with:

plan_budget Rate-limited

plan_budget 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "plan_budget": {
      "limits": [
        {
          "counter": "plan_budget_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect FeatureBoard, apply this rule, and every plan_budget call is checked against it from then on.

FAQ

Questions about plan_budget

What does the plan_budget tool do? +

Map a token budget onto the priority-ordered open queue BEFORE spending it: assigns tickets to days (greedy load-balance),. 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.

How do I enforce a policy on plan_budget? +

Register the FeatureBoard MCP server in PolicyLayer and add a rule for plan_budget: 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.

What risk level is plan_budget? +

plan_budget is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit plan_budget? +

Yes. Add a rate_limit block to the plan_budget 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.

How do I block plan_budget completely? +

Set action: deny in the PolicyLayer policy for plan_budget. 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.

What MCP server provides plan_budget? +

plan_budget 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.

KEEP EXPLORING

More on FeatureBoard, and thousands of servers like it.

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emit_variant_plan on 0sec →team_manager_plan_room on Team Manager MCP → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →