US Brand Signal Cross-Tabulator

US Brand Signal Cross-Tabulator builds a deterministic two-dimensional count table from buyer-supplied opaque rows. It is useful for compact segmentation such as eventType x status, brand x reviewState, or sourceClass x outcome when an agent already owns the observations.

The Actor does not fetch a website, resolve an ID, identify a person or company, verify a source, or infer causality. It only counts the rows in the request.

What you submit and receive

You submit 1 to 100 unique rows. Each row has:

• rowId: a unique printable ASCII identifier;
• rowDimension: one of at most 15 printable ASCII row categories;
• columnDimension: one of at most 15 printable ASCII column categories.

You receive one Dataset report with:

• every row/column combination, including cells with count 0;
• rowTotals and columnTotals;
• rowPercentBasisPoints, columnPercentBasisPoints, and overallPercentBasisPoints for every cell;
• explicit denominator definitions, sorted values, and SHA-256 digests;
• a truthful OUTPUT receipt after one confirmed Dataset write.

Basis points are integers from 0 to 10000. For example, 5000 means 50%. Each percentage is rounded independently to the nearest basis point. The report states the denominator for each field: the row total, the column total, or all input rows.

Run it

1. Open Try for free in the Actor Console.
2. Paste the exact JSON shape shown in the Input section.
3. Start the run and read the one report row from the Dataset.
4. Read the terminal delivery receipt from OUTPUT.

The runnable prefill is also available in examples/input.json and public-task.json.

Pricing

Pay per event: $0.005 per run start plus $0.010 per delivered result on the FREE tier. The result event is emitted only after one confirmed Dataset write. The Actor checks that the buyer cap covers both charges before processing.

Tier	Discount	Start	Delivered result
FREE	0%	$0.00500	$0.01000
BRONZE	5%	$0.00475	$0.00950
SILVER	10%	$0.00450	$0.00900
GOLD	15%	$0.00425	$0.00850
PLATINUM	18%	$0.00410	$0.00820
DIAMOND	20%	$0.00400	$0.00800

Invalid input, insufficient cap, uncertain delivery, and an uncharged or multiply charged result are not reported as successful results. The Actor never retries a paid Dataset push.

Freshness and determinism

There is no external freshness because this Actor does not fetch data and does not read the clock. Refresh the rows in your upstream system and rerun when observations change. The same rows always produce the same matrix and digests regardless of input order.

Input

{
  "schemaVersion": "1.0",
  "rows": [
    {"rowId": "observation-001", "rowDimension": "enterprise", "columnDimension": "accepted"},
    {"rowId": "observation-002", "rowDimension": "enterprise", "columnDimension": "review"},
    {"rowId": "observation-003", "rowDimension": "startup", "columnDimension": "accepted"},
    {"rowId": "observation-004", "rowDimension": "startup", "columnDimension": "rejected"},
    {"rowId": "observation-005", "rowDimension": "enterprise", "columnDimension": "accepted"}
  ]
}

Output

The Dataset has one deterministic report item. matrix is sorted by rowDimension, then columnDimension, and contains the full Cartesian product of observed dimensions. OUTPUT contains the terminal delivery receipt and links represented by the Store output schema.

Related public Actors

These Actors can feed or use the same buyer-owned analytics workflow. This Actor does not call them.

Actor	Use it for
US Brand Signal Metrics Aggregator	Summarize numeric signal rows before building a cross-tabulation.
US Brand Signal Brief Composer	Turn a submitted matrix and totals into a bounded brief.
US Brand Action Queue	Convert selected matrix segments into next-action rows.
US Brand Evidence Snapshot Diff	Compare two buyer-supplied matrix or evidence snapshots.
US Brand Offer Evidence Normalizer	Normalize offer evidence before tabulating dimensions.

Limitations

• Dimension values are opaque ASCII IDs and are not treated as names, people, companies, or verified entities.
• The maximum input is 100 rows, 15 unique row dimensions, and 15 unique column dimensions.
• Duplicate row IDs and extra fields fail closed.
• The report is bounded below 64 KiB. A mathematically valid input that would exceed the bound returns output_too_large rather than a partial result.
• There is no network, proxy, BYOK key, LLM, clock, state, child Actor, or Dataset input.
• JSON Schema validates shape; runtime validators additionally enforce sorting, complete zero cells, basis-point reconciliation, and digest integrity.

FAQ

Why are zero cells included? A complete matrix makes absence explicit and lets downstream machines compare shapes without guessing whether a cell was omitted.

What does a basis-point denominator mean? Row basis points use that cell's row total; column basis points use its column total; overall basis points use all submitted rows. The denominators object repeats these definitions in the report.

Does the matrix prove a relationship? No. It is only a count of buyer-supplied rows.

Can I submit URLs or names? The contract accepts opaque ASCII IDs only. The Actor does not resolve URLs or identity.

What happens after uncertain delivery? The Actor records a non-success terminal receipt and does not issue a second Dataset write.

Built by zinin.