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thinkneo_simulate_savings

Read-onlyIdempotent

Simulate how much your organization would save on AI costs using ThinkNEO Smart Router. Enter your current monthly AI spend and primary model, and see estimated monthly and annual savings with a recommended model mix. No authentication required — try it now!

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
primary_modelNoYour primary model: 'gpt-4o', 'claude-opus-4', 'claude-sonnet-4', 'gpt-4.1', or 'gemini-2.5-pro'gpt-4o
monthly_ai_spendYesYour current monthly AI API spend in USD (e.g., 5000.00)
task_distributionNoJSON string of task distribution, e.g., '{"chat": 0.3, "summarization": 0.2, "code_generation": 0.2, "classification": 0.15, "analysis": 0.1, "translation": 0.05}'. Values should sum to ~1.0. Omit for default enterprise distribution.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changed
    • removedInput schema / properties / current_provider
      Removed value: -{
-  "default": "openai",
-  "description": "Primary provider: openai, anthropic, google, azure",
-  "title": "Current Provider",
-  "type": "string"
-}
    • addedInput schema / properties / monthly_ai_spend
      Added value: +{
+  "description": "Your current monthly AI API spend in USD (e.g., 5000.00)",
+  "title": "Monthly Ai Spend",
+  "type": "number"
+}
    • removedInput schema / properties / monthly_ai_spend_usd
      Removed value: -{
-  "description": "Current monthly AI spend in USD",
-  "title": "Monthly Ai Spend Usd",
-  "type": "number"
-}
    • addedInput schema / properties / primary_model
      Added value: +{
+  "default": "gpt-4o",
+  "description": "Your primary model: 'gpt-4o', 'claude-opus-4', 'claude-sonnet-4', 'gpt-4.1', or 'gemini-2.5-pro'",
+  "title": "Primary Model",
+  "type": "string"
+}
    • addedInput schema / properties / task_distribution
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "JSON string of task distribution, e.g., '{\"chat\": 0.3, \"summarization\": 0.2, \"code_generation\": 0.2, \"classification\": 0.15, \"analysis\": 0.1, \"translation\": 0.05}'. Values should sum to ~1.0. Omit for default enterprise distribution.",
+  "title": "Task Distribution"
+}
    • changedInput schema / required
      Previous value: -[
-  "monthly_ai_spend_usd"
-]New value: +[
+  "monthly_ai_spend"
+]
  2. Changed6 schema fields changed
    • addedInput schema / properties / current_provider
      Added value: +{
+  "default": "openai",
+  "description": "Primary provider: openai, anthropic, google, azure",
+  "title": "Current Provider",
+  "type": "string"
+}
    • removedInput schema / properties / monthly_ai_spend
      Removed value: -{
-  "description": "Your current monthly AI API spend in USD (e.g., 5000.00)",
-  "title": "Monthly Ai Spend",
-  "type": "number"
-}
    • addedInput schema / properties / monthly_ai_spend_usd
      Added value: +{
+  "description": "Current monthly AI spend in USD",
+  "title": "Monthly Ai Spend Usd",
+  "type": "number"
+}
    • removedInput schema / properties / primary_model
      Removed value: -{
-  "default": "gpt-4o",
-  "description": "Your primary model: 'gpt-4o', 'claude-opus-4', 'claude-sonnet-4', 'gpt-4.1', or 'gemini-2.5-pro'",
-  "title": "Primary Model",
-  "type": "string"
-}
    • removedInput schema / properties / task_distribution
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "JSON string of task distribution, e.g., '{\"chat\": 0.3, \"summarization\": 0.2, \"code_generation\": 0.2, \"classification\": 0.15, \"analysis\": 0.1, \"translation\": 0.05}'. Values should sum to ~1.0. Omit for default enterprise distribution.",
-  "title": "Task Distribution"
-}
    • changedInput schema / required
      Previous value: -[
-  "monthly_ai_spend"
-]New value: +[
+  "monthly_ai_spend_usd"
+]
  3. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly and idempotent, and the description adds that no authentication is required and that it takes user inputs to produce estimates. This extends the behavioral context without contradiction.

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

Conciseness5/5

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

Two sentences deliver purpose, inputs, outputs, and auth requirement without redundancy. The 'try it now!' phrase is minor and does not detract from the clarity.

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 an output schema and rich annotations, the description adequately covers the tool's function and key inputs/outputs. It omits task_distribution, but that is fully documented in the schema, and the overall context is complete enough for a low-complexity simulation tool.

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?

The schema provides full descriptions for all three parameters, including defaults, examples, and a JSON example for task_distribution. The description only repeats 'current monthly AI spend' and 'primary model,' so it adds no meaningful parameter detail beyond the schema.

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 clearly states the tool simulates savings on AI costs using ThinkNEO Smart Router, with specific inputs (monthly AI spend, primary model) and outputs (monthly/annual savings, recommended model mix). The verb 'simulate' distinguishes it from reporting or audit siblings.

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 explicitly says 'No authentication required — try it now!' which indicates it's for quick prospective estimates. However, it doesn't explicitly contrast with sibling tools like thinkneo_get_savings_report or thinkneo_agent_roi.

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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