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Glama

Taokeh MCP server

Bank review queue

bank_review_queue
Read-only

The IMPORTED BANK REGISTER — the rows that came in on a bank or card statement, in ANY status, defaulting to the ones still awaiting review. By default (no status) it is exactly the unreviewed queue it has always been: the unposted rows of one statement, or of the latest imported statement if you don't name one. Pass status to read the settled history instead — 'confirmed' (categorised, not yet posted), 'posted' (in the ledger), 'ignored' (the owner set them aside) or 'all'. Pass from/to WITHOUT a statementId to read a DATE WINDOW across every statement this company has imported, rather than one statement; the payload then says scope:'window' and statement is null. A window holding more than 1000 rows still awaiting review is refused with the count — narrow the dates or name a statementId; settled history has no such ceiling. ⛔ HAND-RECORDED settlements are NEVER here whatever you pass: a receipt or supplier payment typed into Taokeh by hand has no statement behind it, and this tool is the imported register only. To find those, use search_documents with docType:'payment'. Each row still awaiting review carries Taokeh's LIVE suggested category + contact, a confidence score (0–1) and a plain-language reason, computed the SAME way the in-app Banking → Review screen computes them. A suggestion does NOT come only from the tenant's transaction history: the owner can write a standing RULE for a payer (What Taokeh has learned → Bank rules), and such a rule beats what Taokeh worked out on its own — those rows' reasons read "You set this rule on " rather than "Learned: … (×N)". If a suggestion looks unlike the payer's history, the rule is usually why; say so instead of calling the history wrong. Sorted lowest-confidence first (the ones that need a human eye), capped at 200 with an honest truncation note, plus per-confidence bucket counts so you can say e.g. "46 are mechanical, 13 need eyes". A row can also carry possibleDuplicateOf: a receipt or supplier payment the owner already recorded BY HAND that looks like the same money as this imported line (same account, same amount, within three days) — it is only a resemblance, Taokeh decides nothing from it, and you should say so rather than propose a category for money that may already be in the books. What you CAN do with a row: review it, explain it, and PROPOSE a category with draft_bank_classification — and, for the two categories whose account the owner picks by hand (OTHER and INTERNAL_TRANSFER), the LEDGER ACCOUNT too. Your proposal is written to the row as an "AI suggestion" the owner sees on Banking → Review, with your proposed account pre-selected in their dropdown and marked as yours; rows already carrying a proposal from you come back here as yourProposal, so you can see what you told them. What you can NEVER do: CONFIRM or POST a row — and proposing the account changes nothing about that: it fills a dropdown, the owner still clicks. Accepting a category and posting each line is always a human click in Taokeh; hand the owner the review link. (Since 2026-08-19 the owner can also accept Taokeh's confident suggestions, and post confirmed lines, from the /go command bar's approval deck — still one human tap either way. YOUR OWN proposals are accepted only on Banking → Review, where your reasons are shown.) ⚠ SETTLED ROWS CARRY NO SUGGESTION. A row that has already been confirmed, posted or ignored comes back with suggestedCategory, suggestedContact, confidence, reason and possibleDuplicateOf all NULL — the classifier is not re-run over decided history, because a fresh guess printed beside a decision the owner already made reads as a second opinion on settled books. Those rows carry what was actually DECIDED instead: category, glAccount ({code,name}, null if the row has none), contact (the customer or supplier on the row), journalEntryId (null unless posted), splits (where the amount was divided across accounts) and allocations (the invoices or bills the money settled). statusCounts always reports how the rows in scope break down by status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoLatest transaction date (YYYY-MM-DD).
fromNoEarliest transaction date (YYYY-MM-DD). WITHOUT a statementId, from/to widen the read to a DATE WINDOW across every imported statement — 'what did the bank register show in July' rather than 'what is on this one statement'.
statusNoWhich rows: 'unreviewed' (DEFAULT — everything not yet posted or ignored, i.e. the review queue), 'confirmed', 'posted', 'ignored', or 'all'. Only unreviewed rows carry suggestions; the rest carry what was decided.
statementIdNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • addedInput schema / properties / from
      Added value: +{
      +  "description": "Earliest transaction date (YYYY-MM-DD). WITHOUT a statementId, from/to widen the read to a DATE WINDOW across every imported statement — 'what did the bank register show in July' rather than 'what is on this one statement'.",
      +  "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      +  "type": "string"
      +}
    • addedInput schema / properties / status
      Added value: +{
      +  "description": "Which rows: 'unreviewed' (DEFAULT — everything not yet posted or ignored, i.e. the review queue), 'confirmed', 'posted', 'ignored', or 'all'. Only unreviewed rows carry suggestions; the rest carry what was decided.",
      +  "type": "string"
      +}
    • addedInput schema / properties / to
      Added value: +{
      +  "description": "Latest transaction date (YYYY-MM-DD).",
      +  "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark readOnlyHint: true, and the description adds substantial behavioral detail beyond that: the 1000-row window ceiling with refusal, the 200-row cap with truncation note, null suggestions on settled rows, possibleDuplicateOf being only a resemblance, and the rule that confirmation/posting always requires human action. There is no contradiction with the read-only annotation; the tool only reads, while proposals are made through another tool.

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?

The description is long and dense, but it is front-loaded with the core purpose, uses visual markers like ⛔ and ⚠, and structures the content around defaults, windows, exclusions, suggestions, and settled rows. Some phrases are repetitive or contain asides that could be trimmed, but the length is largely justified by the number of modes and caveats an agent must understand.

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?

There is no output schema, so the description carries the full burden of explaining return semantics. It covers scope and statement fields, statusCounts, confidence buckets, row-level fields for both unreviewed and settled rows, possibleDuplicateOf, yourProposal, truncation behavior, and the refusal condition for large windows. Combined with the explicit routing to sibling tools, this is enough for an agent to invoke the tool correctly without guessing.

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?

Schema coverage is 75% and the schema's statementId description is corrupted, so the description must compensate and largely does. It explains the meaning and default of status, the date-window behavior of from/to without statementId, and the role of statementId in scoping and the row cap. The description adds real semantics beyond the schema, though statementId itself is not given a dedicated, direct definition.

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 identifies the tool as the imported bank register/review queue and explains that it returns statement rows in any status, defaulting to unreviewed ones. It differentiates itself from search_documents for hand-recorded settlements and from draft_bank_classification for proposing categories, so an agent can select it correctly among the many sibling tools.

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

Usage Guidelines5/5

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

The description gives explicit selection criteria: use the default for the unreviewed queue, pass status for settled history, pass from/to without statementId for a date window, and use search_documents with docType:'payment' for hand-recorded entries. It also states what the tool can and cannot do, naming draft_bank_classification as the separate tool for proposals.

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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