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Glama

ExpenseBot

by io.github.TotesMagotes

get_client_advance_balances

Read-only

Read the same per-client advance balances shown in ExpenseBot's Client advances section. Use for questions like 'how much of Acme's advance remains?', 'which client floats are still open?', or 'do I owe a client a refund?'. A negative ledger balance means money remains to refund; a positive balance means the client owes the user. Returns the existing app handoff for Refund leftover or Bill Client. Read-only: never records a refund, creates an invoice, or recomputes the ledger in model prose.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clientNameNoOptional client name or canonical Client tag. Omit to list every open balance backed by a recorded client advance.
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 / clientName / description
      Previous value: -"Optional client name or canonical Client tag. Omit to list all open balances."New value: +"Optional client name or canonical Client tag. Omit to list every open balance backed by a recorded client advance."
    • removedInput schema / properties / days
      Removed value: -{
-  "description": "Lookback window in days (default 365).",
-  "maximum": 3650,
-  "minimum": 30,
-  "type": "integer"
-}
  3. Added

TDQS

A4.3/5.0
Behavior5/5

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

The description adds meaningful behavior beyond the annotations: it explains the ledger sign semantics (negative = refund remains, positive = client owes), states validated that it 'never records a refund, creates an invoice, or recomputes the ledger in model prose,' and reveals the return value (the existing app handoff for Refund leftover or Bill Client). None of these details are in the schema or 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?

Four sentences with each earning its place: purpose, usage examples, balance semantics, and output/read-only guarantee. Slightly more verbose than strictly necessary and the read-only clause partially repeats the annotations, but the text is well-structured and front-loaded.

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?

With no output schema, the description does the needed work on return behavior: it explains sign semantics and the returned app handoff. It does not fully describe the return shape but a reasonable level of completeness for an agent to select and invoke the tool confidently.

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%; the schema already documents both clientName (with the 'omit to list every open balance' behavior) and clientEmail. The description adds no parameter-level guidance, so the 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 opens with a specific verb and resource: 'Read the same per-client advance balances shown in ExpenseBot's Client Advances section.' It includes concrete example queries ('how much of Acme's advance remains?', 'which client floats are still open?') that make it unmistakable distinct from siblings like get_client_invoice, get_income_summary, and get_credits_refunds.

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?

Clear when-to-use context is given through example user questions, which is strong routing guidance. However, it does not explicitly name alternatives or state when-not-to-use, leaving a small overlap ambiguity with get_credits_refunds for the 'do I owe a client a refund?' use case.

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