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Banking Assistant (Metabind demo)

get_transactions

get_transactions
Read-onlyIdempotent

Raw transactions by category or merchant, ~12 months of history. Numbers to reason with — to display, use transaction_list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNo'recent' is newest-first and is what a plain list wants. Use 'largest' for "my biggest transactions" — a window can hold hundreds of rows, so date order buries them.recent
limitNoMax transactions to return. Pass 0 for totals and counts only — much cheaper when you need the figures to reason with rather than to list.
periodNoTime window. Ignored when startDate/endDate are given. The feed covers ~25 months, so a 1y window has a full prior year to compare against.mtd
endDateNoWindow end, YYYY-MM-DD. Defaults to today.
categoryNoCategory or plain term to filter by, e.g. 'Food & Dining', 'restaurants', 'rent', 'gas', 'income'. A merchant name here is resolved as a merchant. Omit or leave empty for all categories.
merchantNoSingle store or brand to filter by, e.g. 'Whole Foods', 'Netflix', 'Shell'. Combine with category to narrow further.
startDateNoWindow start, YYYY-MM-DD. Defaults to 30 days before endDate.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
shownNo
categoryNo
standoutsNo
top_itemsNo
periodLabelNo
total_spentNo
transactionsNo
change_vs_prev_pctNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / required
      Added value: +[]
  2. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds the 'raw' vs 'aggregated' distinction and a retention claim, but nothing about pagination, cost, or precision. Note the stated '~12 months of history' conflicts with the schema's own period description ('feed covers ~25 months'), which is a description-vs-schema inconsistency rather than an annotation contradiction.

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?

Two terse fragments with zero filler; the core capability leads and the routing hint is front-loaded rather than buried. Every clause carries information.

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?

An output schema exists, so return structure need not be described. However, the description's history claim (~12 months) contradicts the schema's ~25-month feed, which can mislead an agent planning an 'all' or 1y window, and the description omits that the tool also serves count/total-only requests. Usable but not fully trustworthy for planning.

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%, with sort, limit, period, category and merchant all richly documented in-schema (including the limit=0 totals trick and date precedence). The description only echoes the category/merchant filters, adding essentially nothing the schema has not already said — baseline 3 is correct.

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 and resource ('Raw transactions'), the two filter axes (category or merchant), and explicitly routes display-oriented callers to the sibling transaction_list. An agent can distinguish this from transaction_list without opening either 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?

Gives an explicit when/when-not pair: use this for 'numbers to reason with', use transaction_list 'to display'. It does not distinguish this tool from the other analytical siblings (spending_breakdown, subscriptions, net_worth_trend), so it stops short of fully disambiguating the tool set.

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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