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Glama

ExpenseBot

by io.github.TotesMagotes

correct_expenses

Destructive

Safely correct the category, business purpose, or explicit attendees on an exact bounded set of recorded expenses. Examples: 'categorize these as Travel', 'add Client kickoff dinner as the business purpose for these meals', or 'add Fred, Rob, and Lamar to last night's business meal'. First use search_expenses to identify the exact rows, then pass their full expenseId values. A grounded preview is automatic: first call with confirm omitted/false, show the exact count and proposed before-to-after changes, and ask once for approval. Only after explicit approval repeat the same operationId, selection, and change with confirm:true. A premature confirm:true is converted to preview. Attendee names must come explicitly from the user; never infer them. attendeeMode add preserves existing attendees, while replace substitutes only the attendee segment. Business purpose and attendees preserve the structured Notes field, including card, description, inbox, and other typed segments. Formula Notes and changes that exceed the Notes limit are skipped safely. The confirmed result reports applied/conflicted/failed counts and supports Undo. This tool does not omit duplicates, change amounts or dates, infer business context, or run broad Calendar matching. For unsupported or more than 100-row cleanup, send the user to https://www.expensebot.ai/review-expenses?source=mcp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
undoNoUndo a completed correction within its Undo window.
changeNoExactly one correction. The selected type determines which matching value field is required.
statusNoRead operation status using operationId.
confirmNoOmit/false for preview; true only after explicit approval.
selectionNoExact expenses returned by search_expenses and approved for this bounded correction.
operationIdYesStable idempotency key generated once for preview and reused unchanged.

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. Changed8 schema fields changed
    • addedInput schema / properties / change / properties / attendees / description
      Added value: +"Attendee names explicitly supplied by the user when type is attendees; never infer names."
    • addedInput schema / properties / change / properties / businessPurpose / description
      Added value: +"User-supplied business purpose to apply when type is businessPurpose."
    • addedInput schema / properties / change / properties / category / description
      Added value: +"Configured expense category to apply when type is category."
    • addedInput schema / properties / change / properties / type / description
      Added value: +"The one correction kind to apply to every exact selected expense."
    • addedInput schema / properties / selection / description
      Added value: +"Exact expenses returned by search_expenses and approved for this bounded correction."
    • addedInput schema / properties / selection / properties / items / description
      Added value: +"One exact receipt identity per selected expense; never broaden this list after preview."
    • addedInput schema / properties / selection / properties / items / items / properties / expected / properties / category / description
      Added value: +"Current category observed before preview for conflict detection."
    • addedInput schema / properties / selection / properties / items / items / properties / expected / properties / notes / description
      Added value: +"Current structured Notes value observed before preview for conflict detection."
  3. First observed

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations (destructiveHint=true, readOnlyHint=false), it discloses important behavioral traits: premature confirm:true is converted to preview, operationId is an idempotency key reused unchanged, attendee names must come from the user, Notes segments are preserved, and over-limit changes are skipped safely. It also specifies that results report applied/conflicted/failed counts and support Undo, providing rich behavioral depth without contradicting the annotations.

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 front-loaded with purpose and examples, then proceeds logically through workflow, parameter semantics, boundaries, and fallback. The length is justified by the tool's complexity (6 params, nested objects, destructive confirmation flow) and every sentence earns its place with no redundancy.

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 no output schema and a destructive, stateful tool, the description fully compensates: it describes the confirmation flow, the contents of a preview (exact count and before-to-after changes), result reporting (applied/conflicted/failed, Undo), and behavioral boundaries. The operational fallback for unsupported cases and the 100-row limit also make the tool safe to invoke.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds substantial value on top: it explains that receiptId values are the exact full expenseIds from search_expenses, attendeeMode 'add' preserves while 'replace' substitutes, operationId must be generated once and reused, and expected fields are used for conflicting detection. It also grounds the stateful preview/confirm protocol in parameter terms.

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 and resource ('correct the category, business purpose, or explicit attendees on an exact bounded set of recorded expenses') and reinforces it with concrete examples. It clearly distinguishes itself from sibling tools like update_expense or search_expenses through the bounded-batch scoping and preview requirements.

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?

The description explicitly prescribes the workflow: first use search_expenses to identify rows, then pass full expenseId values, preview with confirm omitted/false, and confirm true only after explicit approval. It also gives when-not guidance (does not change amounts/dates, omit duplicates, infer business context, or run broad calendar matching) and a fallback URL for unsupported or >100-row cleanup.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All ExpenseBot toolsInspect
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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