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ExpenseBot

by io.github.TotesMagotes

add_income_from_csv

Import income from a CSV/TSV/text export (Stripe, PayPal, Square, Cash App, Venmo, OnlyFans, Patreon, Clips4Sale, Ko-fi, Gumroad, Etsy, Uber/Lyft/DoorDash driver exports, bank statements, and similar; max 500 KB). Same two-step contract as add_income_from_file: STEP 1 call with csvContent and WITHOUT confirm parses the file with the same platform-agnostic importer as the app's Add Income screen (platform detection, fee handling, refunds, source aliases, ISO dates) and returns a duplicate-checked preview with a previewId. NOTHING is saved in step 1. Show the user the parsed rows and duplicates, then STEP 2 call again with confirm: true and the previewId to write exactly those rows, optionally with user-approved selectedIndexes, keepBothIndexes, rowEdits, tag, or bulkNote. Flagged duplicates are skipped unless the user explicitly keeps them. The preview expires after 15 minutes and an expired or unknown previewId never writes. After a successful confirm, show the returned spreadsheetUrl and reviewIncomeUrl.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoOptional client/project tag. In step 1 it pre-fills the staged rows; in step 2 it applies to the confirmed selection.
confirmNoStep 2 only: true writes the staged rows. Omit it (with previewId absent) to parse and preview without writing.
csvTextNoLegacy fallback for MCP clients that send raw CSV/TSV/text content inline. ChatGPT should use csvContent.
bulkNoteNoStep 2 only: one note (max 120 chars) prepended to every confirmed row's Notes, same as the app's 'Add note to all entries'.
rowEditsNoStep 2 only: user-approved corrections, at most 50 rows. Fields: date (ISO YYYY-MM-DD), source, amount, currency, category, paymentMethod, description, notes, reference, fees, taxCollected, tag.
previewIdNoStep 2 only: the previewId returned by the step-1 call.
csvContentNoAttached CSV/TSV/text file supplied by ChatGPT for step 1. The server downloads and decodes the attachment securely.
paymentMethodNoFallback payment rail for rows where the parser found none (Cash, Check, Bank transfer, Wallet app, Credit/Debit card, Payment processor, or Other).
keepBothIndexesNoStep 2 only: preview indexes of duplicate-flagged rows the user explicitly wants to keep anyway (the app's 'Keep Both').
selectedIndexesNoStep 2 only: preview row indexes to write. Omit to write all staged rows.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "description": "Standard ExpenseBot tool result envelope. `message` is the human-readable summary the AI cites; `data` is the structured payload (totals, breakdowns, ids, etc.). On failure, `success` is false and `error` carries a code/message/hint triple.",
-  "properties": {
-    "data": {
-      "additionalProperties": true,
-      "description": "Structured payload. Shape varies per tool — common keys: total, breakdown, comparison, sampleMeta, ids, expenseId, reportId, signupUrl, results.",
-      "type": "object"
-    },
-    "error": {
-      "additionalProperties": true,
-      "description": "Present only when success === false.",
-      "properties": {
-        "code": {
-          "type": "string"
-        },
-        "hint": {
-          "type": "string"
-        },
-        "message": {
-          "type": "string"
-        }
-      },
-      "type": "object"
-    },
-    "message": {
-      "description": "Human-readable result text. Always present on success; prefer rendering this verbatim before any further reasoning.",
-      "type": "string"
-    },
-    "sampleMeta": {
-      "additionalProperties": true,
-      "description": "Set when the underlying dataset was truncated. isTruncated=true means the agent saw a sample of `sampleCount` of `totalCount` rows; aggregate totals are still accurate.",
-      "properties": {
-        "isTruncated": {
-          "type": "boolean"
-        },
-        "sampleCount": {
-          "type": "integer"
-        },
-        "totalCount": {
-          "type": "integer"
-        }
-      },
-      "type": "object"
-    },
-    "success": {
-      "description": "False on tool errors; check before reading `data`.",
-      "type": "boolean"
-    }
-  },
-  "type": "object"
-}New value: +null
  2. Changed6 schema fields changed
    • changedInput schema / properties / csvContent / description
      Previous value: -"Raw CSV/TSV/text content (step 1). On ChatGPT you may pass the attached file reference object directly; the server fetches and decodes the bytes."New value: +"Attached CSV/TSV/text file supplied by ChatGPT for step 1. The server downloads and decodes the attachment securely."
    • addedInput schema / properties / csvContent / properties
      Added value: +{
+  "download_url": {
+    "description": "Temporary HTTPS URL supplied by ChatGPT for downloading the attachment.",
+    "format": "uri",
+    "type": "string"
+  },
+  "file_id": {
+    "description": "Attachment identifier supplied by ChatGPT.",
+    "type": "string"
+  },
+  "file_name": {
+    "description": "Original attachment filename supplied by ChatGPT.",
+    "type": "string"
+  },
+  "mime_type": {
+    "description": "Attachment MIME type supplied by ChatGPT.",
+    "type": "string"
+  }
+}
    • addedInput schema / properties / csvContent / required
      Added value: +[
+  "download_url",
+  "file_id"
+]
    • changedInput schema / properties / csvContent / type
      Previous value: -"string"New value: +"object"
    • addedInput schema / properties / csvText
      Added value: +{
+  "description": "Legacy fallback for MCP clients that send raw CSV/TSV/text content inline. ChatGPT should use csvContent.",
+  "type": "string"
+}
    • addedInput schema / properties / rowEdits / items / properties / fields / description
      Added value: +"Only the user-approved income fields to replace on this staged row: date, source, amount, currency, category, paymentMethod, description, notes, reference, fees, taxCollected, or tag."
  3. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description goes far beyond the annotations by stating that step 1 saves nothing, duplicates are skipped unless explicitly kept, previews expire after 15 minutes, and invalid preview IDs never write. This gives an agent a realistic model of the tool's side effects and could not be inferred from annotations alone.

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?

The description is long but densely structured: it front-loads the purpose and file limits, uses STEP 1/STEP 2 markers to impose order, and every sentence contributes either contract behavior or parameter usage. For a 10-parameter, two-phase tool, this length is justified.

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?

The description covers the full lifecycle: file submission, parsing, preview, duplicate handling, user edits, expiration, confirm behavior, and the URLs to show after success. Given no output schema and the complexity of 10 parameters, this completeness is strong.

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 100%, so the baseline is already 3, but the description adds cross-parameter semantics by explaining which parameters belong to which step and how selectedIndexes, keepBothIndexes, rowEdits, tag, and bulkNote interact with the preview. It does not need to repeat schema-level details because those are already complete.

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 opens with a specific verb and resource: 'Import income from a CSV/TSV/text export,' and names common sources such as Stripe, PayPal, Square, and bank statements. It clearly distinguishes this tool from manual income entry and references the related add_income_from_file workflow while maintaining its own file-import identity.

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 spells out exactly when to call the tool: step 1 with csvContent and no confirm for parsing, then step 2 with confirm:true and previewId to write rows. It does not explicitly say 'use this instead of X,' but the two-step contract and duplicate-handling guidance make the intended usage clear.

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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TDQS

A3.6/5.0
Disambiguation3/5

Most tools are explicitly scoped, but several analytics/retrieval tools overlap in purpose, such as get_spending_summary vs get_deep_analytics vs get_monthly_books_review, and generic search vs search_expenses vs search_knowledge. The detailed descriptions help, but an agent still has to carefully choose between near-equivalent options like correct_expenses vs update_expense and the three add_income variants.

Naming Consistency5/5

Tool names consistently use lower_snake_case with a recognizable verb prefix: get_*, list_*, add_*, create_*, check_*, scan_*, search_*, and whatif_*. Minor exceptions like fetch and search are still terse retrieval verbs rather than a different naming style, so the overall pattern is predictable.

Tool Count1/5

With 59 tools, this exceeds the 50+ threshold for an extreme tool count and creates a heavy selection surface for an agent. Even though ExpenseBot covers many subdomains, many get_/list_/add_ variants could be consolidated into fewer parameterized tools. The count undermines the otherwise clear naming structure.

Completeness3/5

The surface is strong for creating, reading, and updating expenses, reports, invoices, and Gmail scans, but there are notable lifecycle gaps: no delete/void tools for expenses, income, reports, or invoices, and no update tool for income. Several descriptions explicitly redirect unsupported edits to the web app, confirming that the assistant cannot complete those workflows directly.

Resources