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Estimate cashback on AI subscriptions

vest_estimate_cashback
Read-onlyIdempotent

Estimate how much cashback a user would earn on their AI tool subscriptions via Vest. Pass subscriptions with monthly costs; Vest accounts for loyalty tier (5–20% depending on total spend). Use when the user asks 'how much could I save?', 'what's my cashback estimate?', or is evaluating whether to join Vest. No API key required. Do NOT use this to recommend tools — use vest_build_stack. Do NOT use this to check what the user already has on Vest — use vest_get_account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subscriptionsYesList of current or planned AI tool subscriptions.
include_alternatesYesWhen true, attempt to include cheaper alternatives for each tool.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare safe, read-only behavior. The description adds useful context (no API key required, loyalty tier logic 5-20%). Does not contradict annotations. Minor omission: no mention of return format or errors, but output schema exists.

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?

Five sentences, each earning its place: overview, usage guidance, two explicit negatives with sibling references. Concise and front-loaded.

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 complexity (nested array, 2 required params), annotations, and output schema presence, description covers purpose, usage, exclusions, and key behavioral traits. Could mention output structure minimally but output schema handles that.

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 baseline 3. Description reinforces that subscriptions need monthly costs and mentions loyalty tier, but adds limited new meaning beyond schema descriptions.

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?

Description states a specific verb ('estimate') and resource ('cashback on AI subscriptions via Vest'), and explicitly distinguishes from sibling tools like vest_build_stack and vest_get_account. It is clear and unambiguous.

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?

Description provides explicit when-to-use scenarios ('how much could I save?', 'what's my cashback estimate?') and when-not-to-use with specific alternative tools. This is exemplary guidance.

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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