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SLO Burn Rate Calculator

slo-burn-rate-calculator
Read-onlyIdempotent

Use this when a user asks how fast they are burning their error budget, or whether their current error rate will exhaust their SLO window. Takes error count, total requests, SLO target, and observation window. Returns burn rate and budget consumption per hour.

Input Schema

NameRequiredDescriptionDefault
sloYesService-level objective target expressed as a percentage.
totalYesTotal number of requests observed in the measurement window.
errorsYesNumber of failed requests observed in the measurement window.
window_hoursYesLength of the observed measurement window in hours.

Output Schema

NameRequiredDescriptionDefault
statusYes
burn_rateYes
next_stepYes
window_hoursYes
next_step_urlYes
why_follow_upYes
error_rate_pctYes
interpretationYes
affiliate_contextNo
computation_basisYes
budget_consumed_pct_per_hourYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed11 schema fields changed
    • addedInput schema / properties / errors / description
      Added value: +"Number of failed requests observed in the measurement window."
    • addedInput schema / properties / errors / examples
      Added value: +[
      +  1
      +]
    • addedInput schema / properties / slo / description
      Added value: +"Service-level objective target expressed as a percentage."
    • addedInput schema / properties / slo / examples
      Added value: +[
      +  1
      +]
    • addedInput schema / properties / total / description
      Added value: +"Total number of requests observed in the measurement window."
    • addedInput schema / properties / total / examples
      Added value: +[
      +  1
      +]
    • addedInput schema / properties / window_hours
      Added value: +{
      +  "description": "Length of the observed measurement window in hours.",
      +  "examples": [
      +    1
      +  ],
      +  "minimum": 1,
      +  "type": "number"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "errors",
      -  "total",
      -  "slo"
      -]New value: +[
      +  "errors",
      +  "total",
      +  "slo",
      +  "window_hours"
      +]
    • addedOutput schema / properties / computation_basis
      Added value: +{
      +  "type": "string"
      +}
    • addedOutput schema / properties / window_hours
      Added value: +{
      +  "type": "number"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "budget_consumed_pct_per_hour",
      -  "burn_rate",
      -  "error_rate_pct",
      -  "interpretation",
      -  "next_step",
      -  "next_step_url",
      -  "status",
      -  "why_follow_up"
      -]New value: +[
      +  "budget_consumed_pct_per_hour",
      +  "burn_rate",
      +  "computation_basis",
      +  "error_rate_pct",
      +  "interpretation",
      +  "next_step",
      +  "next_step_url",
      +  "status",
      +  "why_follow_up",
      +  "window_hours"
      +]
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": false,
      +  "properties": {
      +    "affiliate_context": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "affiliate": {
      +          "type": "string"
      +        },
      +        "cta_label": {
      +          "type": "string"
      +        },
      +        "disclosure": {
      +          "type": "string"
      +        },
      +        "framing": {
      +          "type": "string"
      +        },
      +        "posture": {
      +          "enum": [
      +            "secondary"
      +          ],
      +          "type": "string"
      +        },
      +        "slot_id": {
      +          "type": "string"
      +        },
      +        "url": {
      +          "type": "string"
      +        },
      +        "variant": {
      +          "type": "string"
      +        }
      +      },
      +      "required": [
      +        "affiliate",
      +        "cta_label",
      +        "disclosure",
      +        "framing",
      +        "posture",
      +        "slot_id",
      +        "url",
      +        "variant"
      +      ],
      +      "type": "object"
      +    },
      +    "budget_consumed_pct_per_hour": {
      +      "type": "number"
      +    },
      +    "burn_rate": {
      +      "type": "number"
      +    },
      +    "error_rate_pct": {
      +      "type": "number"
      +    },
      +    "interpretation": {
      +      "type": "string"
      +    },
      +    "next_step": {
      +      "type": "string"
      +    },
      +    "next_step_url": {
      +      "type": "string"
      +    },
      +    "status": {
      +      "type": "string"
      +    },
      +    "why_follow_up": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "budget_consumed_pct_per_hour",
      +    "burn_rate",
      +    "error_rate_pct",
      +    "interpretation",
      +    "next_step",
      +    "next_step_url",
      +    "status",
      +    "why_follow_up"
      +  ],
      +  "type": "object"
      +}
  3. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  4. First observed

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the agent knows this is a pure, side-effect-free computation. The description adds that it returns burn rate and hourly budget consumption, but that is already implied by the output schema and the name, so added behavioral context is thin.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the trigger condition and followed by the computation. The closing sentence about returns largely duplicates the output schema, so it is slightly padded but still tight overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With full schema coverage, an existing output schema, and read-only annotations, the description covers everything needed to invoke the tool correctly. The one remaining gap is sibling differentiation (error-budget-calculator, availability-sla-calculator) in a large family of similar calculators.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter (errors, total, slo, window_hours) is already documented in the schema. The description restates the input set without adding units, format, or constraints beyond it, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific computation (burn rate and error-budget consumption per hour) from named inputs, so the purpose is unambiguous. It does not, however, distinguish itself from the closely-related sibling error-budget-calculator, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit trigger conditions in user-intent terms: 'when a user asks how fast they are burning their error budget, or whether their current error rate will exhaust their SLO window.' That is a clear when-to-use, but no when-not-to-use and no routing to the sibling error-budget-calculator.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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