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Bankstatemently

Get Credit Balance (processing quota)

get_credits
Read-only

Your remaining Bankstatemently credits — the processing quota, NOT credit/debit transactions. Use for: how many credits do I have, remaining pages, plan limits, quota, how many pages can I upload. 1 credit = 1 page of bank statement processing. Also reports your plan's operational limits (max pages per upload, max upload size, daily spend cap) so you can size a multi-file batch correctly before starting it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
planYes
limitYes
planIdYes
balanceYes
summaryYes
creditsExpireAtYes

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds value by stating it also reports 'plan's operational limits (max pages per upload, max upload size, daily spend cap)', which goes beyond the basic read-only nature and helps set expectations for the returned data. This is useful context beyond what annotations provide.

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 concise yet information-dense. It opens with the core definition, then provides usage examples, a critical clarification, and a note about additional returned data. Every sentence serves a purpose with no fluff, and the structure is front-loaded with the most important information.

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?

For a no-parameter, read-only tool with an output schema, the description covers all needed context: what it returns (credits and limits), when to use it, and how it relates to batch sizing. The presence of an output schema means return values are already documented, and the description fills in the operational intent. Nothing essential is missing for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there are no parameter semantics to describe. The schema covers 100% of parameters (none), and the baseline for a 0-parameter tool is 4. The description does not need to add parameter-level details, and it correctly focuses on the returned information.

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 precisely states the tool returns 'remaining Bankstatemently credits' and explicitly distinguishes these from 'credit/debit transactions', eliminating a common confusion. It names the resource and the verb, and the clarification that it is a processing quota makes it distinct from potential sibling tools that might handle transactions.

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 description provides concrete use cases ('how many credits do I have, remaining pages, plan limits, quota, how many pages can I upload') and explicitly warns it is NOT for credit/debit transactions. It also advises using it before starting a multi-file batch to size correctly. However, it doesn't mention when to prefer this over specific siblings, though the sibling tools are clearly distinct in purpose.

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

A4/5.0
Disambiguation4/5

Core tools are cleanly separated by resource: statements, transactions, transfers, credits, and benchmark all have dedicated entry points. The five analytics tools (aggregate, group_by, compare, time_series, top_n) share metric/filter language, but their distinct output shapes and careful descriptions prevent major confusion, with only group_by vs. time_series/top_n occasionally overlapping.

Naming Consistency4/5

Most tools follow a clear snake_case verb_noun pattern such as convert_statement, list_transactions, rate_statement, and dismiss_statement. The analytics tools (aggregate, compare, group_by, time_series, top_n) break that pattern, but they are still recognizable, consistently styled, and form a meaningful cluster.

Tool Count4/5

At 16 tools, this is slightly above the typical 3-15 well-scoped range, but the server covers a broad workflow: upload, conversion, retrieval, categorization, analytics, transfer matching, rating, credits, and benchmarking. Each tool maps to a distinct capability, so the count feels justified rather than bloated.

Completeness4/5

The tool surface covers the full statement lifecycle from upload and conversion through retrieval, categorization, analysis, rating, and dismissal, plus useful side capabilities like credits and benchmark evaluation. Minor gaps exist—no permanent deletion and no way to manually edit category mappings—but dismiss_statement and categorize_statement provide adequate workarounds.