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Glama

ExpenseBot

by io.github.TotesMagotes

get_credits_refunds

Read-only

List card refunds, cashback/rewards, and statement credits that ExpenseBot has already recorded — either as negative expenses or matched against the original charge. Examples: 'did my refund come through', 'show my statement credits', 'was that return recorded'. Returns the most recent items (default 25, newest first); narrow with dateRange. Read-only: it never scans cards, changes review decisions, or adds rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results to return (default 25, max 100).
dateRangeNoOptional open-ended or closed window to narrow results. Supply startDate, endDate, or both; supplied bounds are inclusive YYYY-MM-DD dates.
clientEmailNoClient account email. Accountants may use this only for an accepted ExpenseBot client.

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. Changed4 schema fields changed
    • addedInput schema / properties / dateRange / additionalProperties
      Added value: +false
    • changedInput schema / properties / dateRange / description
      Previous value: -"Optional window to narrow results. Both bounds inclusive, YYYY-MM-DD."New value: +"Optional open-ended or closed window to narrow results. Supply startDate, endDate, or both; supplied bounds are inclusive YYYY-MM-DD dates."
    • addedInput schema / properties / dateRange / properties / endDate / format
      Added value: +"date"
    • addedInput schema / properties / dateRange / properties / startDate / format
      Added value: +"date"
  3. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint=true annotation, the description openly states it never scans cards, changes review decisions, or adds rows, and explains returned items are negative expenses or matched against the original charge. It also discloses ordering and default count (newest first, default 25), which adds concrete behavioral detail beyond structured annotations.

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?

The description is concise with the primary action front-loaded, followed by clarifying examples and key behavioral constraints. It contains no fluff, though the two example-heavy sentences could be slightly tightened; still well-organized and readable.

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?

Given no output schema, the description clearly states what is returned ('most recent items', default 25, newest first) and provides enough guidance on optional use of dateRange. It lacks a detailed shape of the returned items, but the description is adequate for a simple read-only list tool.

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 description coverage is 100%, so the input schema already documents all three parameters. The description mentions default 25 and dateRange narrowing, but does not add substantial meaning beyond the schema; thus baseline 3 is appropriate.

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 explicitly states 'List card refunds, cashback/rewards, and statement credits that ExpenseBot has already recorded', naming both the action and the specific resource. It further disambiguates with user intent examples and a positive claim about scope, so an agent can distinguish it from sibling tools like get_income_summary or get_spending_summary.

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?

The description gives clear usage context through example user queries and emphasizes it only reads already-recorded data. It does not explicitly name an alternative tool or state 'use X instead', but 'Read-only: it never scans cards, changes review decisions, or adds rows' conveys when not to use it relative to scanning or review workflows.

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