util_error_budget_plan

Convert an SLO percentage and request window into allowed failure budget.

SERVERDelx Mcp A2a SOURCEhttps://api.delx.ai/v1/mcp

Medium RISK CLASS

Category Write

Parameters 22 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-davidmosiah-delx-mcp-a2a/util-error-budget-plan.md

WHAT IT DOES

What util_error_budget_plan does on Delx Mcp A2a

AI agents use util_error_budget_plan to create or update resources in Delx Mcp A2a, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Delx Mcp A2a environment.

Parameter	Type	Required	Description
`slo_percent`	number	Yes	Service level objective as a percent (e.g. 99.9).
`window_requests`	number	Yes	Request count in the error-budget window.

Parameters from the server's own tool schema.

RISK

Why util_error_budget_plan is rated Medium

An AI agent can call util_error_budget_plan faster than any human can review: one bad instruction and it creates or modifies resources in Delx Mcp A2a by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs util_error_budget_plan safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Delx Mcp A2a, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For util_error_budget_plan, this is the rule to start with:

util_error_budget_plan Rate-limited

util_error_budget_plan 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": {
    "util_error_budget_plan": {
      "limits": [
        {
          "counter": "util_error_budget_plan_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 Delx Mcp A2a, apply this rule, and every util_error_budget_plan call is checked against it from then on.

FAQ

Questions about util_error_budget_plan

What does the util_error_budget_plan tool do? +

Convert an SLO percentage and request window into allowed failure budget. It is categorised as a Write tool in the Delx Mcp A2a MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does util_error_budget_plan accept? +

util_error_budget_plan accepts 2 parameters: slo_percent, window_requests. Required: slo_percent, window_requests. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on util_error_budget_plan? +

Register the Delx Mcp A2a MCP server in PolicyLayer and add a rule for util_error_budget_plan: 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 Delx Mcp A2a. Nothing to install.

What risk level is util_error_budget_plan? +

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

Can I rate-limit util_error_budget_plan? +

Yes. Add a rate_limit block to the util_error_budget_plan 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 util_error_budget_plan completely? +

Set action: deny in the PolicyLayer policy for util_error_budget_plan. 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 util_error_budget_plan? +

util_error_budget_plan is provided by the Delx Mcp A2a MCP server (https://api.delx.ai/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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