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Dayze — Life Context

Import Venmo Gmail

import_venmo_gmail

Search connected Gmail for Venmo receipts and write log_transaction rows with external_id=venmo-gmail-{gmail_id} (idempotent). Optional dry_run, max_results, query, mirror_event, account. Prefer this over calendar-only Money · digs. Requires mail.read on an API key or non-ChatGPT OAuth connection. ChatGPT profiles do not grant mail.read or list this tool. ($0.15; API key required)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoAlias for account
queryNoOverride Gmail search (default from:venmo.com paid/payment)
accountNoMailbox email or connection id
dry_runNo
request_idNoClient idempotency key (retries return original result).
max_resultsNo
mirror_eventNoAlso create Money · calendar annotations
idempotency_keyNoAlias for request_id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
accountNoThe Dayze account this data belongs to. With more than one Dayze connection, name it in the answer.
resultsYes
scannedYes
skippedYes
importedYes
duplicatesYes
provenanceNoWhich connector wrote the record and which connected Dayze account received it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / account
      Added value: +{
      +  "additionalProperties": false,
      +  "description": "The Dayze account this data belongs to. With more than one Dayze connection, name it in the answer.",
      +  "properties": {
      +    "display_name": {
      +      "description": "Account display name.",
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "handle": {
      +      "description": "Account handle, e.g. @goh.",
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "note": {
      +      "description": "How to disclose the account to the user.",
      +      "type": "string"
      +    },
      +    "qa_fixture": {
      +      "description": "True for a known QA test account: its records are fixture data, not a real life.",
      +      "type": "boolean"
      +    }
      +  },
      +  "required": [
      +    "handle",
      +    "display_name",
      +    "qa_fixture",
      +    "note"
      +  ],
      +  "type": "object"
      +}
    • addedOutput schema / properties / provenance
      Added value: +{
      +  "additionalProperties": false,
      +  "description": "Which connector wrote the record and which connected Dayze account received it.",
      +  "properties": {
      +    "account": {
      +      "additionalProperties": false,
      +      "description": "The Dayze account this data belongs to. With more than one Dayze connection, name it in the answer.",
      +      "properties": {
      +        "display_name": {
      +          "description": "Account display name.",
      +          "type": [
      +            "string",
      +            "null"
      +          ]
      +        },
      +        "handle": {
      +          "description": "Account handle, e.g. @goh.",
      +          "type": [
      +            "string",
      +            "null"
      +          ]
      +        },
      +        "note": {
      +          "description": "How to disclose the account to the user.",
      +          "type": "string"
      +        },
      +        "qa_fixture": {
      +          "description": "True for a known QA test account: its records are fixture data, not a real life.",
      +          "type": "boolean"
      +        }
      +      },
      +      "required": [
      +        "handle",
      +        "display_name",
      +        "qa_fixture",
      +        "note"
      +      ],
      +      "type": "object"
      +    },
      +    "channel": {
      +      "description": "Always mcp_connector.",
      +      "type": "string"
      +    },
      +    "connector": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "kind": {
      +          "description": "oauth or api_key.",
      +          "type": "string"
      +        },
      +        "name": {
      +          "description": "The connected app or API-key label shown to the account owner.",
      +          "type": "string"
      +        }
      +      },
      +      "required": [
      +        "kind",
      +        "name"
      +      ],
      +      "type": "object"
      +    },
      +    "source": {
      +      "description": "chatgpt for ChatGPT OAuth writes; mcp for another OAuth app or API key.",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "source",
      +    "channel",
      +    "connector",
      +    "account"
      +  ],
      +  "type": "object"
      +}
  2. Changed2 schema fields changed
    • addedInput schema / properties / account
      Added value: +{
      +  "description": "Mailbox email or connection id",
      +  "type": "string"
      +}
    • addedInput schema / properties / email
      Added value: +{
      +  "description": "Alias for account",
      +  "type": "string"
      +}
  3. Added

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=false). It discloses the idempotency key format, dry_run availability, required mail.read scope, that ChatGPT profiles neither grant mail.read nor list the tool, and the $0.15 cost. That is exactly the operational context an agent needs before invoking a write tool.

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?

Front-loaded with the core action and its idempotency guarantee, then conditions and cost. Dense but every clause carries weight; the parenthetical cost/auth notes are slightly crammed but not wasteful.

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?

An output schema exists, so return values need not be described, and the description covers the write behavior, idempotency, auth requirements, and profile limitations. Nothing an agent needs to call it correctly is missing.

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?

With 75% schema coverage the schema already documents several params; the description adds the semantics that matter most (idempotent external_id format, dry_run, mirror_event, query, account) and flags them as optional. The email/idempotency_key aliases are left to the schema, which is a minor omission.

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?

States a specific verb+resource: searches connected Gmail for Venmo receipts and writes log_transaction rows. The external_id pattern (venmo-gmail-{gmail_id}) and the sibling imports (import_uber_gmail, import_rideshare_gmail) make the scope unmistakable.

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?

Explicitly routes the agent: 'Prefer this over calendar-only Money · digs,' and states the prerequisite (mail.read on an API key or non-ChatGPT OAuth). It does not explicitly contrast with import_uber_gmail/import_rideshare_gmail, but the resource names make the split self-evident, so this is clear context rather than a full when/when-not matrix.

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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