CounselorAI

Aid estimate explainer

aid

Explain what a family is likely to see across a list of schools and why, in plain language. An explanation for a counselor to walk a family through, never an official determination, and the output says so.

Cost: about 73 credits (~$0.073) per call.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "aid"
  }
}

Input Schema

Name	Required	Description
`income`	No	Household income, as the family stated it.
`context`	No	Household situation that affects the estimate.
`schoolCount`	No	How many schools are being compared.
`studentName`	No	The student this is about. Used in the output text.
`fafsaContext`	No	What is already known from the FAFSA, including the SAI if it has come back.
`repayContext`	No	What the family has said about borrowing and what they can carry.
`schoolSummaries`	No	One line per school: name, cost of attendance, anything already known about the offer.

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 2, 2026

TDQS

A4/5.0

Behavior4/5

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

The description adds useful behavioral detail beyond the annotations: the call costs about 73 credits, and the output itself includes a statement that it is not an official determination. The annotation flags are not very informative, so this extra context carries real weight.

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 compact and well structured: the first sentence states the core purpose, the second adds the key limitation and output behavior, and the cost line is a relevant operational detail. No filler or repetition.

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?

For a text-generation tool with no output schema, the description sufficiently conveys the audience, output style, non-official status, and cost. It could be stronger on output structure or explicit sibling routing, but the essential calling context is present.

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 seven parameters are already documented in the input schema. The description does not add much parameter-level meaning, but it does provide the general context that these inputs describe the family and schools being compared. Baseline 3 is appropriate.

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 purpose: explain expected aid across a list of schools in plain language for a counselor to walk a family through. The 'never an official determination' qualifier adds useful precision, though it does not explicitly differentiate from sibling tools.

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 clear context for use: this is a walkthrough explanation for counselors, and it explicitly rules out use as an official determination. It does not name sibling alternatives or state conditions for choosing a different tool, but the intended use is well established.

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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