earnrate

Compare welcome offers

compare_welcome_offers

Read-only

Ranks the public welcome (sign-up) offers on cards the user doesn't have by first-year value: the bonus at the user's point values minus the first year's annual fee. Use it when the user asks which new card to get or which has the best sign-up bonus. It covers only the cards earnrate knows, offers vary by person, and each offer's note gives the issuer's eligibility rules; pass those caveats on. It doesn't account for what a card would earn on the user's spending.

Input Schema

Name	Required	Description
`kind`	No	cash: cash back cards only. points: points and miles cards only.
`cards`	No	Cards the user named in this conversation, to answer for just those cards without saving anything. Leave out to use the user's saved wallet if they have one; with neither, the answer covers every card earnrate knows.
`business`	No	Business cards instead of personal ones.
`valuation`	No	flat (default): points at their cash-out value, about 1¢. points-heavy: Amex MR and Chase UR at 1.7¢, for people who transfer points to airlines and hotels.
`includeHeld`	No	Include cards already in the wallet.
`noAnnualFee`	No	Only cards with no annual fee.

Output Schema

Name	Required	Description	Default
`notes`	Yes
`offers`	Yes
`withoutOffer`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedNov 1, 2026

addedInput schema / properties / valuation

Added value: +{
+  "description": "flat (default): points at their cash-out value, about 1¢. points-heavy: Amex MR and Chase UR at 1.7¢, for people who transfer points to airlines and hotels.",
+  "enum": [
+    "flat",
+    "points-heavy"
+  ],
+  "type": "string"
+}

addedOutput schema / properties / offers / items / properties / varies
```
Added value: +{
+  "type": "boolean"
+}
```

changedOutput schema / properties / offers / items / required

Previous value: -[
-  "cardId",
-  "cardName",
-  "issuer",
-  "business",
-  "currency",
-  "centsPerUnit",
-  "points",
-  "dollars",
-  "spend",
-  "months",
-  "validTo",
-  "note",
-  "annualFee",
-  "firstYearFee",
-  "bonusValue",
-  "firstYearValue",
-  "held",
-  "lastVerified",
-  "verifiedBy"
-]New value: +[
+  "cardId",
+  "cardName",
+  "issuer",
+  "business",
+  "currency",
+  "centsPerUnit",
+  "points",
+  "dollars",
+  "spend",
+  "months",
+  "validTo",
+  "varies",
+  "note",
+  "annualFee",
+  "firstYearFee",
+  "bonusValue",
+  "firstYearValue",
+  "held",
+  "lastVerified",
+  "verifiedBy"
+]

First observedOct 31, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations already establish read-only and closed-world behavior, and the description adds meaningful caveats beyond them: coverage is limited to cards earnrate knows, offers vary by person, eligibility rules live in each offer's note and must be passed on, and spending-earn value is excluded. These disclosures materially affect how the agent should present results.

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?

Four tightly written sentences: purpose and formula first, then when to use it, then caveats, then a scope limitation. No sentence is redundant and the most important information is front-loaded.

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?

With an output schema present, full annotation coverage, and complete parameter descriptions, the remaining burden is explaining scope and caveats. The description does that: it states the ranking formula, the known-cards limitation, personalization variability, eligibility-rule notes, and what it ignores.

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 the schema already documents all six parameters thoroughly. The description only glancingly connects to parameters via 'the user's point values' and 'cards the user doesn't have'; it does not need to add more, but it also does not deepen parameter meaning beyond the schema baseline.

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 names a specific verb ('ranks'), resource ('public welcome (sign-up) offers on cards the user doesn't have'), and ranking metric ('first-year value: the bonus at the user's point values minus the first year's annual fee'). It is immediately distinguishable from sibling tools focused on ongoing spending value such as best_card_for_purchase or best_cards_for.

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 a clear trigger ('Use it when the user asks which new card to get or which has the best sign-up bonus') and an implicit exclusion ('It doesn't account for what a card would earn on the user's spending'). It does not explicitly name alternative tools, but the usage boundary is clear enough for selection.

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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