# Publication Proofing — Daily Sum Series + Explicit Missing-Value Fill

> Publication Proofing — Daily Sum Series + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Computes daily sum time series and fills missing values (zero, mean, or median) for publication proofing records tracking checked and flagged pages, across up to 200 rows with two independent reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-writing-18-145?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/publication-proofing-daily-sum-series-explicit-missing-value-fill-69488628
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5ZsSuY0Dfvt4V1G4f6DsL

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability publication-proofing-daily-sum-series-explicit-missing-value-fill-69488628 -d '<json body>'
```

Example prompt: I have publication proofing records for two document groups over the past week — each row has a date, checked_pages, and flagged_pages counts, but some rows have nulls. Can you compute the daily sum series for checked_pages and fill any missing values using median, then give me two reports covering up to 200 rows?

## When to prefer this

Choose this endpoint when you have publication proofing records (checked_pages, flagged_pages) and need both a daily sum time series and explicit missing-value imputation in a single low-cost call. It is ideal for editorial or document QA workflows where datasets are small (≤200 rows), no external data lookups are needed, and the analysis is entirely self-contained on supplied data.

## Known failure modes

- Rows exceed 200-item limit — request rejected
- Date field does not match YYYY-MM-DD pattern — validation error
- Both checked_pages and flagged_pages are null for all rows — imputation produces no meaningful output
- Invalid fill method enum value — schema validation error
- row_id missing or empty — required field error

## How this service works

Publication proofing — Daily sum series + Explicit missing-value fill: Daily sum series + Explicit missing-value fill for supplied publication proofing records (checked_pages, flagged_pages). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two independent analytical reports: (1) a daily sum time series aggregating the selected field (checked_pages or flagged_pages) by date, and (2) an explicit missing-value fill report replacing nulls with the chosen method (zero, mean, or median). Both reports are computed locally from the supplied rows with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "document_group",
     "date",
     "checked_pages",
     "flagged_pages"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "checked_pages": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "flagged_pages": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "document_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "checked_pages": 10,
     "flagged_pages": 1,
     "document_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "checked_pages": 20,
     "flagged_pages": 2,
     "document_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "checked_pages": 15,
     "flagged_pages": 3,
     "document_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "checked_pages": 30,
     "flagged_pages": 4,
     "document_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "checked_pages",
    "flagged_pages"
   ],
   "type": "string",
   "default": "checked_pages"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/publication-proofing-daily-sum-series-explicit-missing-value-fill-69488628/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)