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bankstatemently

bankstatemently

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by bankstatemently
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Remote

Transaction Time Series

time_series
Read-only

Group transactions into weekly or monthly buckets and apply a metric to analyze spending or income trends. Narrow by account, product, or date range.

Instructions

Compute a time series by grouping transactions into week or month buckets and applying a metric — useful for trends. Scope defaults to all your completed statements; pass "scope" to narrow to specific accounts/products and/or a date range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoOptional structural scope (WHO × WHEN). Omit to search across all your completed statements. "accounts" is a list of account/product chips ({ kind: "account" | "product", id }, the id of an account descriptor or product returned by a tool); "dateRange" bounds by transaction date (YYYY-MM-DD).
bucketYesBucket size.
filterNoSubset of transactions to operate on. All fields are optional and combined with AND logic.
metricYesMetric per bucket.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv2.0.0
    • addedInput schema / properties / filter / additionalProperties
      Added value: +false
    • removedInput schema / properties / filter / properties / accounts
      Removed value: -{
-  "description": "Account number slugs to include.",
-  "items": {
-    "type": "string"
-  },
-  "type": "array"
-}
    • changedInput schema / properties / scope / description
      Previous value: -"Optional structural scope (WHO × WHEN). Omit to search across all your completed statements. \"accounts\" is a list of account/product chips (kind + identityKey); \"dateRange\" bounds by transaction date (YYYY-MM-DD)."New value: +"Optional structural scope (WHO × WHEN). Omit to search across all your completed statements. \"accounts\" is a list of account/product chips ({ kind: \"account\" | \"product\", id }, the id of an account descriptor or product returned by a tool); \"dateRange\" bounds by transaction date (YYYY-MM-DD)."
    • changedInput schema / properties / scope / properties / accounts / description
      Previous value: -"Account/product chips (kind + identityKey) to scope to. Empty = all accounts."New value: +"Account/product id chips (kind + id) to scope to. Empty = all accounts."
    • changedInput schema / properties / scope / properties / accounts / items / oneOf
      Previous value: -[
-  {
-    "properties": {
-      "anchorContentHash": {
-        "description": "Document-anchored lookup when present (results page); omit for a user-scoped lookup (workspace surfaces).",
-        "type": "string"
-      },
-      "identityKey": {
-        "description": "Canonical account identity key (accountIdentityKey), never a raw DB UUID.",
-        "minLength": 1,
-        "type": "string"
-      },
-      "kind": {
-        "const": "account",
-        "description": "This chip addresses a single account.",
-        "type": "string"
-      },
-      "label": {
-        "description": "Display label for this chip.",
-        "type": "string"
-      }
-    },
-    "required": [
-      "kind",
-      "identityKey"
-    ],
-    "type": "object"
-  },
-  {
-    "properties": {
-      "identityKey": {
-        "description": "Product slug.",
-        "minLength": 1,
-        "type": "string"
-      },
-      "kind": {
-        "const": "product",
-        "description": "This chip addresses a product and expands to its child accounts.",
-        "type": "string"
-      },
-      "label": {
-        "description": "Display label for this chip.",
-        "type": "string"
-      }
-    },
-    "required": [
-      "kind",
-      "identityKey"
-    ],
-    "type": "object"
-  }
-]New value: +[
+  {
+    "additionalProperties": false,
+    "properties": {
+      "id": {
+        "description": "The account id: the `id` of an account descriptor returned by a tool, or of a statement tool `accounts[]` entry.",
+        "format": "uuid",
+        "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
+        "type": "string"
+      },
+      "kind": {
+        "const": "account",
+        "description": "This chip addresses a single account.",
+        "type": "string"
+      }
+    },
+    "required": [
+      "kind",
+      "id"
+    ],
+    "type": "object"
+  },
+  {
+    "additionalProperties": false,
+    "properties": {
+      "id": {
+        "description": "The product id: the `id` of a product returned by a statement tool (`get_statement` / `convert_statement`, `products[].id`).",
+        "format": "uuid",
+        "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
+        "type": "string"
+      },
+      "kind": {
+        "const": "product",
+        "description": "This chip addresses a product and expands to its child accounts.",
+        "type": "string"
+      }
+    },
+    "required": [
+      "kind",
+      "id"
+    ],
+    "type": "object"
+  }
+]
  2. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and closed-world, so the safety profile is covered. The description adds one genuine behavioral fact beyond that — the default scope spans all completed statements — but says nothing about output shape, bucketing edge cases, or empty-result behavior.

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?

Two sentences, front-loaded with the core operation and followed by the default/override behavior. No filler, though the em-dash aside about trends is marginal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a nested-scope analytical tool with no output schema, the description covers the input contract adequately via the schema but never hints at the return shape (e.g. bucketed metric series) or how buckets without data behave. Adequate but with a clear gap for an agent reasoning about results.

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 scope, bucket, metric, and filter semantics in detail. The description only restates the scope narrowing behavior and the week/month bucketing, adding no syntax or format detail beyond the schema; baseline 3 applies.

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?

States a specific verb+resource combination: grouping transactions into week/month buckets and applying a metric, plus the intent ('useful for trends'). It is clear what the tool computes, though it does not explicitly differentiate itself from siblings like aggregate, group_by, or top_n.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives useful default context ('scope defaults to all your completed statements; pass scope to narrow'), which tells the agent what happens when scope is omitted. However, it never says when to prefer this over aggregate, group_by, or top_n, so sibling selection is left to inference.

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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