Bankstatemently

Rate Statement Conversion

rate_statement

Report how well a previously converted bank statement was parsed: submit a 1-5 rating, optionally with structured feedback (only accepted when the rating is 3 or below) and use-case tags. Calling this again for the same document updates your existing rating and clears any previous feedback tied to it. Returns the stored rating state in the response — there is no separate tool to read your own rating back. Every response includes a "summary" field: use it as the single source of truth for what happened.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`rating`	Yes
`feedback`	No
`use_case`	No
`document_id`	Yes
`export_format`	No
`use_case_other`	No
`feedback_categories`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`hint`	No
`error`	No
`rating`	No
`status`	Yes
`message`	No
`summary`	No
`useCase`	No
`documentId`	No
`hasFeedback`	No
`useCaseOther`	No

TDQS

A4.3/5.0

Behavior5/5

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

The description discloses behavioral details beyond the annotations: it modifies state (updates rating, clears feedback), returns the stored rating state, and includes a summary field as the source of truth. This goes beyond the annotations' readOnly=false and destructiveHint=false, providing transparency about side effects.

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 and well-structured, starting with the main purpose and then adding behavioral details. It contains no unnecessary information and is easy to parse.

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?

Given the schema has 7 parameters, the description covers less than half. It provides context for rating and feedback but leaves export_format and feedback_categories unexplained. The output schema is not shown, but the description mentions a summary field, so it's partially complete.

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?

The description explains rating, feedback, and use-case tags, but omits explanations for export_format and feedback_categories. It also does not explicitly mention document_id, though it is implied by the context. Thus, parameter coverage is incomplete.

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 clearly states the tool's purpose: rating how well a previously converted bank statement was parsed. It distinguishes itself from sibling tools by focusing on post-conversion feedback, making its role unambiguous.

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 useful usage guidance, noting that calling again updates the rating and clears previous feedback, and that no separate read tool exists. However, it does not explicitly contrast with other tools like evaluate_benchmark, though the context implies when it should be used.

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.

Rate Statement Conversion

Input Schema

Output Schema

TDQS

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TDQS

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