ExpenseBot

get_subscription_audit

Read-only

Subscription audit — wraps the Subscription Auditor engine to find recurring charges, duplicates, price increases, and trial-conversion suspects in the user's expenses. Examples: 'recurring subscriptions', 'duplicate subscriptions', 'price increases', 'trial conversions', 'subscriptions over $20/month'. Returns: { message, data: { recurring, duplicates, priceIncreases, trialConversions, totalMonthlyCost, sampleMeta? } }.

Input Schema

TableJSON Schema

Name	Required	Description
`focus`	No	Narrow the audit to a single category (default: all)
`query`	No	Natural language subscription question (e.g., 'find duplicate subscriptions', 'price increases this year')
`dateRange`	No	Time period filter. Use exactly one variant — pick the shape that matches the user's phrasing.

Output Schema

TableJSON Schema

Name	Required	Description
`data`	No
`message`	No
`success`	No	Present only on the error branch (out of scope) / async path.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 9, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "Success returns message + data with the computed summary; success is not emitted on the inline analytics path.",
+  "properties": {
+    "data": {
+      "additionalProperties": true,
+      "type": [
+        "object",
+        "null"
+      ]
+    },
+    "message": {
+      "type": "string"
+    },
+    "success": {
+      "description": "Present only on the error branch (out of scope) / async path.",
+      "type": "boolean"
+    }
+  },
+  "required": [],
+  "type": "object"
+}

Changed1 schema field changedAug 25, 2026

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

First observedAug 10, 2026

TDQS

A4.1/5.0

Behavior4/5

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

The structured annotations already say readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description meaningfully adds that the tool wraps a 'Subscription Auditor engine' and enumerates the output categories, which helps the agent predict behavior. It does not contradict any annotation.

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 compact and front-loaded: first sentence states the purpose, then a short example list, then a brief return signature. Every part earns its place; no verbose filler or circular wording.

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?

Combined with a rich input schema and an existing output schema, the description supplies the tool's engine, domain keywords, natural-language examples, and return shape. There is no material gap that would prevent an agent from choosing and calling the tool 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 baseline is 3. The description's natural-language examples give useful phrasing for the `query` parameter, but it does not clarify the relationship between `focus` and `query` (e.g., whether query overrides focus or they combine), which is a real semantic gap beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource ('subscriptions') and a clear verb ('audit/find'), enumerates the exact categories it returns (recurring, duplicates, price increases, trial conversions), and gives natural-language examples. It does not explicitly contrast itself with sibling tools like get_spending_summary or get_deep_analytics, so it stops short of a 5.

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 examples ('recurring subscriptions,' 'duplicate subscriptions,' 'subscriptions over $20/month') establish a clear trigger context for an agent deciding to invoke this tool. It does not name alternatives or exclusion conditions, but the type of question this tool handles is unmistakable.

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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