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Get statement import result

well_get_statement_import_result
Read-only

Read the outcome of a bank-statement upload started with well_create_statement_upload, by the document_id that tool returned.

well_create_statement_upload already renders a card from its own result — this tool does not create or redraw it. Call it once, shortly after the client has uploaded the file bytes, to learn what happened. The card refreshes itself as extraction and promotion complete, so a later call here narrates the current state in chat; it never advances or re-renders the card.

  • status "not_found_yet": the upload has not landed yet — a NORMAL result right after minting the slot, not an error. Poll again once the file has been uploaded.

  • status "processing": the file is uploaded and the statement is still being extracted / promoted.

  • status "imported" | "needs_account" | "duplicate" | "skipped" | "failed": the terminal outcome. On "imported", matched_count / review_count / minted_count / already_present_count report the promotion's own snapshot counts, taken once at import time and covering every promotable line of the file disjointly; null on any of them means the row predates count tracking — treat as unknown, never as 0. records lists the minted transactions only — matched or ambiguous lines link an existing transaction and are excluded; graph is the frozen record graph for the same snapshot; records_url opens the workspace's transactions table.

This tool reads only — it changes nothing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idYesThe document_id well_create_statement_upload returned — pre-allocated at mint, before the upload lands.
workspace_idNoTarget workspace. Omit when the token authorizes one workspace. Required when it authorizes several: this read reports one workspace's own figures and will not choose which.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNo
errorNo
graphNoThe frozen record graph for this import, taken from the same snapshot as `records`. Never present on "processing" or "not_found_yet". Like `records`, its counterparty fields are null (frozen before resolution runs) — see `records_url` for the live values.
statusNo
recordsNoTransactions this import minted as new rows — matched or ambiguous lines link an existing transaction and are excluded. Present only on a terminal "imported" result that carries a snapshot. The snapshot freezes at mint time, so `counterparty` is always null here — resolution runs asynchronously after import; open `records_url` for the live resolved value.
successYes
document_idNo
imported_atNo
records_urlNoLogin-gated deep link to the workspace's transactions table — opened on the first minted record when `records` is non-empty, otherwise the plain table.
minted_countNoLines minted as new transactions. Absent means the row predates count tracking — treat as unknown, never as 0.
review_countNoLines skipped as an ambiguous cross-connector match, pending review. Absent means the row predates count tracking — treat as unknown, never as 0.
matched_countNoLines linked to an existing cross-connector transaction. Absent means the row predates count tracking — treat as unknown, never as 0.
resolved_workspaceNoThe workspace that answered, when the caller named none and the token authorizes several.
already_present_countNoLines an earlier import already carried — a partial-overlap re-export mints only the new lines, so the four counts cover the file's promotable lines. Absent means the row predates count tracking — treat as unknown, never as 0.
statement_extraction_idNo

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description goes further by explaining it 'reads only — it changes nothing,' never advances or re-renders the card, and provides detailed status semantics, count snapshot behavior, null handling, and the frozen graph. This is rich behavioral context beyond the annotations.

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 detailed but every sentence earns its place, covering purpose, relationship to the sibling tool, status values, count semantics, and read-only behavior. It is front-loaded with the core purpose and structured with a bulleted list for statuses, making it easy to scan.

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?

With an output schema present and annotations covering safety, the description fully explains the statuses, the meanings of the count fields, the content of records vs. graph, and the read-only nature. Nothing needed for correct invocation or interpretation is missing.

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 input schema already describes both document_id and workspace_id with 100% coverage. The description reinforces that document_id comes from well_create_statement_upload and mentions pre-allocation, but this information is already present in the schema. The description does not add substantially new parameter-level meaning beyond what the schema provides.

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 states a specific verb and resource: 'Read the outcome of a bank-statement upload started with well_create_statement_upload, by the document_id that tool returned.' It clearly distinguishes this from the sibling creation tool by noting it does not create or redraw the card.

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 explicitly instructs when to call the tool: 'Call it once, shortly after the client has uploaded the file bytes, to learn what happened.' It also contrasts with well_create_statement_upload, saying that tool already renders a card and this one does not, and explains polling behavior for 'not_found_yet'.

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

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: CRUD for companies, people, and invoices; financial analytics (cash, cost, runway, holdings); connector management and invocation; schema discovery; querying; reconciliation; and contact channel management. No two tools could be confused for the same action.

Naming Consistency5/5

All tools follow the `well_verb_noun` pattern with consistent verb choices (create, get, list, update, delete, add, remove, run, resolve, query, invoke). The naming is predictable and makes the tool's purpose immediately clear.

Tool Count4/5

With 26 tools, the set is slightly above the ideal 3-15 range, but every tool earns its place given the breadth of the domain (CRM, invoicing, financial analytics, reconciliation, connector management). The count is well-scoped and not excessive.

Completeness4/5

The tool surface covers core CRUD, financial KPIs, reconciliation, and connector management. Minor gaps exist (e.g., no direct tool to update contact channels or manage accounts), but the query and schema tools allow agents to work around them, and the primary workflows are fully supported.

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