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ThinkNEO Control Plane

by ai.thinkneo
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thinkneo_get_savings_report

Read-onlyIdempotent

Get your AI cost savings report. Shows total requests routed, original cost (what you'd have paid with premium models), actual cost, total savings, savings percentage, breakdown by task type, and model distribution. Requires authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoReport period: '7d' (7 days), '30d' (30 days), or '90d' (90 days)30d

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / period
      Added value: +{
+  "default": "30d",
+  "description": "Report period: '7d' (7 days), '30d' (30 days), or '90d' (90 days)",
+  "title": "Period",
+  "type": "string"
+}
    • removedInput schema / properties / workspace
      Removed value: -{
-  "default": "default",
-  "description": "Workspace name or ID",
-  "title": "Workspace",
-  "type": "string"
-}
  2. Changed2 schema fields changed
    • removedInput schema / properties / period
      Removed value: -{
-  "default": "30d",
-  "description": "Report period: '7d' (7 days), '30d' (30 days), or '90d' (90 days)",
-  "title": "Period",
-  "type": "string"
-}
    • addedInput schema / properties / workspace
      Added value: +{
+  "default": "default",
+  "description": "Workspace name or ID",
+  "title": "Workspace",
+  "type": "string"
+}
  3. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds the authentication requirement and specifies the report's content (e.g., original cost, savings percentage), providing context beyond the annotations. It does not contradict any annotation.

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?

The description is three concise sentences: purpose, output contents, and authentication. It is front-loaded with the primary action and contains no filler or redundancy. Every sentence contributes meaningful information.

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

Completeness5/5

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

For a simple read-only report with one optional parameter and an existing output schema, the description covers the purpose, the report's contents, and the authentication requirement. It sufficiently equips an agent to decide whether to use this tool and what to expect, without over-explaining schema-provided details.

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 only parameter (period) is fully documented in the schema with a description covering '7d', '30d', and '90d'. Since schema_description_coverage is 100%, the description need not add parameter semantics. The baseline of 3 is appropriate; the description adds no extra meaning 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 uses a specific verb ('Get') and resource ('AI cost savings report'), and enumerates the exact metrics returned (requests routed, original cost, actual cost, savings, percentages, breakdowns). This clearly differentiates it from sibling tools like budget_status or simulate_savings by focusing on historical cost savings data.

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

Usage Guidelines3/5

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

The description implies usage when one needs an AI cost savings report, but it does not explicitly state when to choose this tool over related siblings (e.g., thinkneo_simulate_savings for projections, thinkneo_get_budget_status for budgets). No exclusions or alternative recommendations are provided, so usage context is only implied.

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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