report_data_issue
Report a data-quality problem you found in an autario dataset or chart (World Bank, FRED, Eurostat, OECD, WHO, IMF, ECB, US Census, SEC or any other publisher in the catalog), so the engine can fix it. Use this during a QA pass when you spot: a dataset that looks truncated / only partially ingested (far fewer rows than the source should have), a unit that contradicts the value range (unit "%" but values in the thousands), nonsensical or wrong column/series labels, an all-identical (zero-variance) column, a published chart that is misleading or plots the wrong series, or data that looks stale. ALWAYS attach the concrete numbers you observed in evidence (e.g. the row count you saw vs. what you expected, the unit, a few sample values) | findings without evidence are not actionable. The engine routes safe types (partial_ingest_suspected, stale, broken_time_col) to an automatic re-ingest on the next refresh; everything else goes to a human review queue. Reporting the same unresolved issue again never creates a duplicate row: it is COUNTED on the existing finding (occurrences in the response), and once the same issue has been reported three times it is escalated into the human review queue. So a repeat is safe, but it is not silent | only report again if you observed the problem again. Requires authentication.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | One-sentence human-readable summary of the issue. | |
| evidence | No | The concrete numbers backing the finding, as a JSON object. Examples: {"rows_seen": 500, "rows_expected": 15000, "source": "World Bank API has ~15k country-year rows"} or {"unit": "%", "value_range": [120, 9800]}. Required for an actionable finding. | |
| severity | No | How bad it is for end users. high = wrong/misleading numbers shown publicly. Default medium. | medium |
| dataset_id | No | The UUID of the dataset the issue is about (from search_datasets / get_dataset_info). Omit only for a chart-level issue with no single owning dataset. | |
| finding_type | Yes | What kind of problem. partial_ingest_suspected = fewer rows than the source has (truncated). stale = data older than it should be. broken_time_col = every row shares one date / a vintage column is used as time. unit_mismatch = declared unit contradicts the numbers. label = wrong/nonsensical column or series names. wrong_series = the wrong or a duplicate series is shown. confusing_chart = a published chart is misleading to end users. zero_variance = all values identical. engine_gap = a systematic parser/engine bug. moved/dead_source = source URL changed or returns 404. |