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Cloud egress cost (FinOps)

cloud_egress_finops
Read-onlyIdempotent

Analyze tiered AWS/GCP public cloud internet data transfer egress pricing versus Cloudflare Zero-Egress Bandwidth Alliance and edge caching proxies, quantifying monthly and annual infrastructure cost savings.

Behavior: Deterministic, idempotent calculation with zero external side effects. Calculates tiered AWS/GCP egress charges ($0.09/GB for first 10TB, $0.085/GB for next 40TB, $0.07/GB for next 100TB, $0.05/GB beyond). Models edge cache offload reduction and compares against Cloudflare zero-egress routing. Returns monthly and annual gross egress costs, post-cache costs, and total net savings.

Usage Guidelines: Use for cloud architecture budgeting, FinOps reviews, and evaluating CDN caching or Cloudflare migration economics. Do not use for LLM token pricing; use ai_token_arbitrage instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_of_dateYesCivil date YYYY-MM-DD selecting the monthly egress price pack. Required; only months with a published pack are answered (otherwise a structured refusal).
cacheHitRatioNoExpected CDN edge caching hit ratio as a decimal (0.0 to 1.0) or percentage (0 to 100%). Default is 0.85 (85%).
monthlyEgressGBNoMonthly public internet outbound data transfer volume in Gigabytes (GB) (e.g. 50000 for 50 TB). Must be positive.
primary_providerNoThe cloud the traffic leaves from, priced from the egress pack in force: 'aws', 'gcp' or 'azure'. Omitted: aws.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo
savingsNo
freshnessNo
disclaimerNo
rate_pack_idNo
statutory_authorityNo
primary_provider_costNo
multi_cloud_comparisonNo
edge_proxy_optimizationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / primary_provider
      Added value: +{
      +  "description": "The cloud the traffic leaves from, priced from the egress pack in force: 'aws', 'gcp' or 'azure'. Omitted: aws.",
      +  "enum": [
      +    "aws",
      +    "gcp",
      +    "azure"
      +  ],
      +  "type": "string"
      +}
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": true,
      +  "properties": {
      +    "disclaimer": {
      +      "type": [
      +        "string",
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "edge_proxy_optimization": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "freshness": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "inputs": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "multi_cloud_comparison": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "primary_provider_cost": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "rate_pack_id": {
      +      "type": [
      +        "string",
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "savings": {
      +      "type": [
      +        "object",
      +        "null"
      +      ]
      +    },
      +    "statutory_authority": {
      +      "type": [
      +        "string",
      +        "number",
      +        "null"
      +      ]
      +    }
      +  },
      +  "type": "object"
      +}
  3. Changed1 schema field changed
    • addedInput schema / required
      Added value: +[
      +  "as_of_date"
      +]
  4. Changed1 schema field changed
    • addedInput schema / properties / as_of_date
      Added value: +{
      +  "description": "Civil date YYYY-MM-DD selecting the monthly egress price pack. Required; only months with a published pack are answered (otherwise a structured refusal).",
      +  "example": "2026-09-26",
      +  "format": "date",
      +  "type": "string"
      +}
  5. Changed2 schema fields changed
    • changedInput schema / properties / cacheHitRatio / description
      Previous value: -"Projected CDN edge cache hit ratio (0.0 to 1.0 or 0 to 100%)"New value: +"Expected CDN edge caching hit ratio as a decimal (0.0 to 1.0) or percentage (0 to 100%). Default is 0.85 (85%)."
    • changedInput schema / properties / monthlyEgressGB / description
      Previous value: -"Monthly internet outbound data transfer in GB (e.g. 50,000 for 50TB)"New value: +"Monthly public internet outbound data transfer volume in Gigabytes (GB) (e.g. 50000 for 50 TB). Must be positive."
  6. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it is a safe, repeatable calculation. The description reinforces this with 'Deterministic, idempotent calculation with zero external side effects,' which is useful but largely redundant with annotations. It adds the pricing tiers and the return structure (monthly/annual gross, post-cache, net savings), which is extra context beyond annotations, but output schema likely covers return values. A 3 is appropriate: some added value but not deep behavioral disclosure.

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?

The description is structured into purpose, behavior, and usage guidelines, with clear front-loading of the core function. It is appropriately sized and every sentence contributes. It could be marginally tighter, but no sentence is wasted.

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?

Given the tool is a read-only calculation with a full input schema, an output schema, and rich annotations, the description covers purpose, behavior, and routing well. The only minor gap is not explaining the structured refusal for missing price packs beyond what the schema already states. Overall, it is complete enough for correct invocation.

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 coverage is 100%, so all four parameters are already documented in the input schema with descriptions, defaults, and enums. The description adds no parameter-level detail beyond what the schema provides. Baseline 3 is correct when the schema does the heavy lifting.

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

Purpose5/5

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

The description opens with a specific verb+resource: 'Analyze tiered AWS/GCP public cloud internet data transfer egress pricing versus Cloudflare Zero-Egress Bandwidth Alliance and edge caching proxies.' It distinguishes itself from all financial siblings by naming the exact cost domain (cloud egress) and even names the closest sibling, ai_token_arbitrage, to disambiguate.

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

Usage Guidelines5/5

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

Usage guidelines are explicit: 'Use for cloud architecture budgeting, FinOps reviews, and evaluating CDN caching or Cloudflare migration economics.' It also provides an explicit exclusion: 'Do not use for LLM token pricing; use ai_token_arbitrage instead.' This is exactly the when-to-use/when-not-to-use/alternative structure that earns a 5.

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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