Skip to main content
Glama

ExpenseBot

by io.github.TotesMagotes
OverviewDiscussionsAdmin

check_tax_deductibility

Read-only

Use this when the user asks for general deduction guidance for an expense type, such as business meals or home-office expenses. Looks up reference rules using the account's tax-country/home settings and current year. A verified rule may return a percentage and reference; unverified rules return unknown/reviewRequired without a percentage. Read-only: it does not classify saved expenses, prepare a return, or determine the user's actual tax liability. Do not use for tax refunds received as income; use get_income_summary for recorded refunds. General guidance is not a tax professional's determination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesBrief expense-type deduction question, e.g. 'are business meals deductible?'; no account numbers or unrelated personal context.
categoryNoOptional expense category to match the reference rule.
merchantNoOptional merchant name only when relevant to the expense type.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
messageNo
successYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / category / description
      Added value: +"Optional expense category to match the reference rule."
    • addedInput schema / properties / merchant / description
      Added value: +"Optional merchant name only when relevant to the expense type."
    • changedInput schema / properties / query / description
      Previous value: -"Deductibility question (e.g., 'is Uber tax deductible', 'home office write-off rules')"New value: +"Brief expense-type deduction question, e.g. 'are business meals deductible?'; no account numbers or unrelated personal context."
  2. Changed1 schema field changed
    • addedOutput schema / properties / data / properties
      Added value: +{
+  "availability": {
+    "enum": [
+      "unknown"
+    ],
+    "type": "string"
+  },
+  "category": {
+    "type": "string"
+  },
+  "country": {
+    "type": "string"
+  },
+  "deductiblePercent": {
+    "maximum": 100,
+    "minimum": 0,
+    "type": "number"
+  },
+  "reviewRequired": {
+    "type": "boolean"
+  }
+}
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "data": {
+      "additionalProperties": true,
+      "type": "object"
+    },
+    "message": {
+      "type": "string"
+    },
+    "success": {
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "success"
+  ],
+  "type": "object"
+}
  4. 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
  5. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description is consistent ('Read-only: it does not classify saved expenses, prepare a return, or determine the user's actual tax liability'). Beyond that it discloses non-obvious behavior the annotations cannot: the lookup keys off the account's tax-country/home settings and current year, and verified rules return a percentage plus reference while unverified rules return unknown/reviewRequired with no percentage.

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?

Front-loads the core 'when to use' before the behavioral and exclusion details, and each sentence carries distinct information (use case, lookup mechanism, return semantics, scope limits, exclusion). It is slightly longer than strictly necessary with some overlapping negative statements ('does not classify... prepare a return... determine liability'), but nothing is filler.

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?

Despite the tool's non-trivial logic, the description covers the trigger, the settings-dependent lookup, the two possible return shapes, the read-only scope, and the sibling alternative. An output schema exists, so return-value documentation is not required, yet the two outcome branches are still flagged, leaving nothing an agent needs missing.

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 query, category, and merchant, including the 'no account numbers or unrelated personal context' constraint. The description adds little parameter-level detail beyond re-emphasizing the expense-type framing, 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?

States a specific verb+resource ('looks up reference rules' for an expense type's deductibility) and scopes it precisely ('general deduction guidance... such as business meals or home-office expenses'). It also explicitly differentiates from a sibling by naming get_income_summary for refunds, so an agent can separate it from the other tools without opening a schema.

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?

Gives an explicit use case ('when the user asks for general deduction guidance for an expense type') and an explicit exclusion with the alternative named ('Do not use for tax refunds received as income; use get_income_summary for recorded refunds'). The routing decision is fully determined.

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

All ExpenseBot toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources