tap

mark_credit

Records whether a card credit was used or confirmed unused this billing period, so the agent stops asking about it until the period resets.

Instructions

Record what the user said about one card credit this period: used = true if they've used it, false if they confirmed it's still unused (Tap then stops asking until the period resets). Credit ids come from optimize_purchase and ask_user.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "card": "<card>",
      "credit": "<credit>",
      "used": "<used>"
    },
    "name": "mark_credit"
  }
}

Input Schema

Name	Required	Description
`card`	Yes
`date`	No	ISO date; defaults to today.
`used`	Yes
`credit`	Yes	The credit's id.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 12, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose a real side effect: used=false causes Tap to stop asking until the period resets, which is behavior an agent cannot infer from the schema. It omits whether a prior record is overwritten, whether the card must already be in the user's set, and what the call returns on failure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence that front-loads the action and then the boolean semantics and id source. The nested parenthetical is slightly crammed but every clause carries information, so nothing is wasted.

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 4-parameter write tool with no annotations and no output schema, the description covers purpose, the consequential side effect, and parameter sourcing. It would be stronger if it stated the effect of re-recording a credit or whether an error is returned for unknown ids.

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 coverage is only 50%, but the description compensates for the two most important gaps: the meaning of the `used` boolean and the provenance of `credit` ids from optimize_purchase and ask_user. Only `card` and `date` rely on the schema alone, and `date` already documents its default.

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 states a specific verb plus resource ('Record what the user said about one card credit this period') and immediately defines the payload semantics of 'used'. It also names where credit ids originate (optimize_purchase, ask_user), distinguishing it from the read-oriented siblings.

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?

Usage is clear from the conditional phrasing: call it when the user reports a credit as used (true) or confirms it is still unused (false). It gives no explicit exclusions or statement of what to do if the state was already recorded, so it stops short of full when/when-not 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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