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Glama

ExpenseBot

by io.github.TotesMagotes

list_client_invoices

Read-only

List the user's issued client invoices (accounts receivable) — who owes them money, how much, and when it is due. Examples: 'which invoices are outstanding', 'what does Acme still owe me', 'any overdue invoices', 'how much am I waiting to get paid'. status accepts 'active' (default), 'open', 'overdue', 'needs_review', 'paid', 'void', 'superseded', or 'all'. Returns invoice numbers, status, totals by currency, delivery state, and private document links. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax invoices to return (default 25, max 100).
statusNoFilter by invoice status (default active/outstanding).
clientNameNoOptional: exact client name (case-insensitive).
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. Changed2 schema fields changed
    • changedInput schema / properties / status / description
      Previous value: -"Filter by invoice status (default open)."New value: +"Filter by invoice status (default active/outstanding)."
    • changedInput schema / properties / status / enum
      Previous value: -[
-  "open",
-  "paid",
-  "all"
-]New value: +[
+  "active",
+  "open",
+  "overdue",
+  "needs_review",
+  "paid",
+  "void",
+  "superseded",
+  "all"
+]
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds useful behavior context beyond that: explicitly states 'Read-only', explains scope is 'user's issued client invoices', describes the returned fields (invoice numbers, status, totals by currency, delivery state, private document links), and reveals that document links are private — a nuance the agent should know. No contradiction with 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 front-loads the action, resource, and purpose, then flows through examples, status values, and returns. It is a single dense paragraph with every sentence earning its place. The status enum repeates what the schema already has, which is minor redundancy, but overall it's well-organised and concise without fluff.

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?

This is a simple, read-only listing tool with 0 required params and no output schema; the description compensates richly by enumerating the return payload (invoice numbers, status, totals per currency, delivery state, private document links) and giving a clear default status. Combined with 100% schema coverage for the remaining parameter semantics, there is nothing essential missing for an agent to call it correctly.

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 schema already documents all four parameters (limit, status, clientName, clientEmail), including the status enum and defaults. The description lists the status options again and mentions the default 'active', which is slightly redundant with the schema but reinforces default behavior. There's no significant added parameter meaning that would raise it above the baseline 3.

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 'List the user's issued client invoices (accounts receivable)' — a specific verb, resource, and scope — and further clarifies with 'who owes them money, how much, and when it is due.' This clearly differentiates it from siblings like get_client_invoice (single-invoice lookup), create_client_invoice (creation), and mark_client_invoice_paid (mutation) without needing to inspect any schema.

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 concrete trigger queries — 'which invoices are outstanding', 'what does Acme still owe me', 'any overdue invoices' — which give an agent strong, clear context for when this tool is the right invocation for user intent. However, it doesn't explicitly name sibling alternatives or state when NOT to use this tool (e.g., a single invoice lookup should go to get_transactions).

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