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Launch529: 529 plans and college costs

Get a 529 plan

get_529_plan
Read-onlyIdempotent

Everything we know about one 529 plan: fees, minimums, investment options, ratings, state tax benefit, restrictions and features. Use the slug from list_529_plans, or the plan's name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planYesA plan slug like 'my529-ut', or part of its name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds useful scope about what data is returned, but says nothing about return format, error behavior, rate limits, or authentication needs. It adds some context beyond annotations but not rich behavioral detail.

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 tight sentences: the first front-loads the returned data categories, and the second gives parameter sourcing advice. No filler, and the most important information (what you get) is first.

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 simple read tool with one required parameter, no output schema, and full annotation coverage, the description is nearly complete: it tells the agent what data will come back and how to supply the plan identifier. It omits error handling or response structure details, but those are minor given the straightforward nature of the operation.

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

Parameters4/5

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

Schema description coverage is 100%, and the schema already explains the parameter accepts a slug or part of a name. The description adds practical provenance by specifying that the slug should come from list_529_plans, which is not present in the schema and helps the agent obtain a valid value.

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 clearly states the tool returns comprehensive details for a single 529 plan and enumerates the specific data categories (fees, minimums, investment options, ratings, state tax benefit, restrictions, features). It implicitly distinguishes from list_529_plans by saying 'one 529 plan' and by referencing that tool for slugs, though it does not mention compare_529_plans.

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 provides a practical hint for supplying the parameter ('Use the slug from list_529_plans, or the plan's name'), which implies the tool is used after listing. However, it gives no explicit guidance on when to choose this tool over compare_529_plans or check_expense, and no when-not conditions.

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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