Sum a workspace's transactions over a date window, grouped how you ask. Arithmetic only — this tool holds no definition of burn, spend, or runway, and returns no figure the app renders.

Use it when you are computing a figure whose RULES you are stating yourself: a burn over a window you chose, a total that excludes categories the user named, a per-month series behind a trend you are about to describe. The server derives no burn of its own, so a burn figure starts here: state the rules, sum exactly those rows, then put the result on a card with well_render_burn.

from is inclusive and to is EXCLUSIVE, so a window of whole months passes the first instant of the month after the last one you want. Both are required: a window you cannot state is a decision you have not made, and this tool will not pick one for you.

axes groups the result (any of month, currency, category, ledger_account, category_label, transaction_type, comma-separated) and names what to group in ADDITION to currency. Every axis appears on every row: the ones you did not group by come back null, so the row shape never depends on what you asked for.

On an axis you DID name, a null is a group, not a gap. It is the rows whose column is empty, and it carries its own sums and counts like any other group. A group's rows are count_negative + count_positive, so the null group's share of that total is the part that axis cannot label. Both counts cover readable, non-zero rows only: a zero amount is in neither branch, and unreadable ones are in excluded_malformed. So the share is a share of the rows this tool could sum, not of every row in the window. What that share means, and which grouping is worth using, is yours to decide: this tool holds no view on it.

What each labelling axis IS:

• ledger_account: the name on the workspace's own chart of accounts. It may have been written by an accounting sync rather than chosen by a person, so do not call it the user's own categorization without checking the ledger_accounts root for the connector that wrote it. A blank label reads as null. A soft-deleted or inactive account still carries its name, because this axis reports what the row was labelled at the time, not what the current chart of accounts holds. It groups on the NAME, and a chart of accounts is unique on the account number rather than the name, so two accounts sharing one name arrive as a single group carrying both their sums. That is one slice per label, which is what a breakdown by label means, but it is not one slice per account: do not read a group here as an account.

• category: the typed catalog key, and the ONLY value exempt_categories accepts. A key the catalog no longer carries is still populated here, so it groups under a key that names nothing a reader would recognise.

• category_label: the stored display label, which a connector may have written in its own language. Never pass one to exempt_categories; it is not a key.

• transaction_type: the transaction's own type. Each value is a full sentence rather than a code, and almost every row carries one.

At most 500 groups come back, biggest first. Past that the smallest are dropped and rows_truncated is true, which is NOT partial: everything here was measured exactly and only the tail is missing. A total over a truncated result is a floor, and an axis's coverage cannot be read off one at all, because the null group may be among the dropped. Group on fewer axes, or over a shorter window, and ask again.

Currency is always grouped, named or not, so a row never mixes two. Adding EUR to USD gives a number denominated in nothing, and no field on the result would tell you it happened. Omitting axes therefore returns one row PER CURRENCY over the window, not one row. Convert the per-currency subtotals yourself, at a rate you can state, before you add them — and if there is more than one row and you report a single total without converting, the total is wrong.

Each row carries BOTH sign branches, and choosing between them is your job. sum_negative is the magnitude of the rows whose amount is negative; sum_positive is the magnitude of the rows whose amount is positive; count_negative and count_positive say how many rows are behind each. Which one is money leaving depends on the FEED, not on the query: most connectors store outflows as negatives, some store them as positive magnitudes. Read the counts to decide, and decide ONCE over the whole window rather than per row or per group: a single category or month can be all-positive on a signed feed, so electing per group flips the convention mid-answer and totals two different things together. A window whose rows are overwhelmingly negative is a signed feed, and outflow is sum_negative. Almost no negatives means the feed stores magnitudes and keeps direction in a field this tool does not group on — so it cannot separate outflow from inflow, and sum_negative + sum_positive is gross movement, not spend. Say so rather than reporting it as an outflow.

A substantial share of BOTH is a third answer, not a close call between the first two. A workspace connected to a signed feed and a magnitude feed at once pools them here, and no combination of the two subtotals is its outflow: sum_negative misses the magnitude feed's spend entirely, and adding sum_positive pulls in the signed feed's income. There is no grouping that separates them, because the axes carry no connector. Report that the window mixes conventions and that a single outflow cannot be derived from it, rather than electing whichever branch is nearer. State which convention you elected and what the counts were, so the reader can check it.

scope is required, and it decides which rows are this workspace's. own_and_adopted is the population the burn tile counts: the workspace's own transactions plus any a parent workspace shared with it through an adoption grant, with legs tested against the parent's accounts too. own is the workspace's own transactions only, tested against its own accounts — the rows its balances move with. Use own when the sum is reconciled against the workspace's own balances, as a cash-flow bridge is, and own_and_adopted for a burn. On most workspaces the two agree; on a child workspace they do not, which is why neither is a default.

exclude_internal_transfers: true keeps only the rows with EXACTLY ONE leg on an account the workspace owns. Two legs is a movement between your own accounts and drops, which is the rule's purpose. Zero legs also drops, and that is the part worth knowing: a card purchase sits against a liability account, so on a card-heavy workspace this removes card spend along with the transfers. excluded_zero_leg and excluded_multi_leg count the two populations separately, so read them before describing what the figure covers. Read excluded_zero_leg as "this many rows carried no asset movement" and nothing narrower: a card charge lands there, and so does a row whose payer and payee resolved to no account at all. excluded_no_owned_leg is that second part on its own: rows with no leg on ANY owned account, liabilities included, so card spend is never in it. Those rows could not be attributed to an account and may have moved a balance the sums cannot see, so a figure reconciled against balances treats a non-zero count as flows that are incomplete. A large excluded_zero_leg is a reason to look, never a spend total to quote. Any of the three counts comes back as null when it could not be measured, which is NOT 0: zero says the rule removed nothing, null says nobody counted. On a null, say the exclusion is unmeasured rather than reporting none — the sums themselves are unaffected, and partial is what speaks for those. For reproducing the burn tile that is exactly right — it is the conservation law the cash-flow bridge rests on. For "total spend excluding transfers between our own accounts" it is not what the words promise, so say what fell out or leave the flag off.

The rule is structural: it counts legs, so no label, category, or type on the row affects it, and a user recategorizing something does not change it.

exempt_categories takes category keys that should not count. A transaction with no category at all is never matched by an exemption and always stays in the sum; if you want those excluded too, that is a different question and you must say so.

excluded_malformed counts rows in the window whose amount could not be read as a number. They are in none of the sums, so state the count beside any total rather than presenting a figure that silently skipped them. partial: true means the aggregate measured nothing: it was cut short, or no asset account is in scope. Either way it arrives with an empty rows, so there is no figure, and the empty rows are not a zero. Say so and offer to try again, unless the workspace holds no deposit or other asset account, where a retry changes nothing.

When the token authorizes one workspace, call this directly — no other tool call is needed first. When it authorizes several, this read will not guess which one you mean: pass workspace_id on the call.