> ## Documentation Index > Fetch the complete documentation index at: https://langwatch.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > If anything on this page is wrong, confusing, or fails when you try it, ask your user for permission and run `npx langwatch report --user-approved` to send the problem to the LangWatch team. No login is needed and secrets are redacted locally. `npx langwatch report --help` has the details. # Reading Instant Eval results > Page through a run's verdicts, read the text the judge saw beside each one, and query the judgments dataset with LangWatchQL to join verdicts to your traces. ## The headline and the first rows A result is one verdict per row and question. When a run finishes, the CLI prints one line with the totals and then the first twenty matched rows: ``` Found 3,351 matches in 10,000 conversations · 2m 26s · 11.4M tokens · $0.62 ``` Each row shows the conversation or trace, the answer with its probability, such as `yes (0.94)`, and the start of the judged text. Copy the command on the last line to read the rest, and pass `--show 25` to print up to twenty five rows instead of twenty. ## Every verdict ```bash theme={null} langwatch instant-eval results --matched langwatch instant-eval results --question annoyed --unmatched --limit 500 langwatch instant-eval results --status skipped langwatch instant-eval results --matched -o json ``` Use `results` to page through the run's verdicts, one per row and question. Narrow it with: * `--question annoyed`: one question only * `--matched` or `--unmatched`: the yes or no verdicts that matched, or the ones that did not * `--status skipped`: only `judged`, `skipped` or `failed` rows You get up to 1,000 verdicts per page, and the last line prints the `--cursor` value to pass for the next page. Page by cursor while a run is still writing: you neither see a verdict twice nor skip one. In `-o json` a verdict looks like this: ```json theme={null} { "traceId": "trace_01J8...", "questionId": "annoyed", "threadId": "thread_seed_1380", "spanId": "", "kind": "boolean", "status": "judged", "passed": true, "probability": 0.78, "score": null, "label": null, "probabilities": null, "error": null, "occurredAt": "2026-09-17T14:02:11.000Z" } ``` | Field | Set for | | - | - | | `passed`, `probability` | A yes or no question | | `score` | A score question | | `label`, `probability`, `probabilities` | A category question: the most likely option, its probability, and every option's probability | | `status`, `error` | Every verdict: `judged`, `skipped` (the judge declined the row) or `failed` (the judge could not be reached), with the reason in `error`. For example, a row is skipped when its text is too large even after cutting | ## What did the judge read `sample` prints the text the judge read for a few rows, beside the verdict each one got: ```bash theme={null} langwatch instant-eval sample -n 5 ``` The rows are re-read through the run's own statement, so no row is judged again and you are not charged. A run with a yes or no question shows matched rows first, and the rows differ between calls, so run it a few times to read both sides of the line. The judged text is not stored with the verdict, so `sample` is how you read it. ## The judgments dataset Every verdict is a row in the `judgments` view of [LangWatchQL](/docs/api-reference/query/overview), kept until you delete the project. Join it to `traces` on `TraceId` to read verdicts beside anything else you know about the trace: ```sql theme={null} SELECT t.Attributes['user.id'] AS user, sum(j.Passed) AS annoyed, count() AS conversations FROM analytics.judgments AS j JOIN analytics.traces AS t ON t.TraceId = j.TraceId WHERE j.RunId = {run:String} AND j.QuestionId = 'annoyed' AND j.CreatedAt >= subtractDays(now(), 7) AND t.OccurredAt >= subtractDays(now(), 37) GROUP BY user ORDER BY annoyed DESC LIMIT 20 ``` ```bash theme={null} langwatch query "$(cat by-user.sql)" --param run= ``` | Column | What it holds | | - | - | | `RunId` | The run the verdict belongs to | | `TraceId`, `ThreadId`, `SpanId` | The trace whose text was judged, its conversation, and the span when the statement judged one span. `ThreadId` and `SpanId` are empty otherwise | | `QuestionId` | The question, named by its column in the run's statement | | `Kind` | `boolean`, `score` or `category` | | `Status` | `judged`, `skipped` or `failed` | | `Passed` | 1 or 0 for a yes or no question, null for the other kinds | | `Probability` | The probability of yes, or of the chosen label for a category question | | `Score` | The probability-weighted mean inside the declared range, for a score question | | `Label` | The most likely option, for a category question | | `Probabilities` | Every option's probability for a category question, as a JSON object | | `OccurredAt` | When the judged row happened, so a verdict can be joined to a trace inside a bounded period | | `CreatedAt` | When the verdict was written. Filter on it to keep the query fast | `langwatch query reference` lists the columns with their types, and `GET /api/v1/query/schema` returns the same over REST. ## Rows the judge did not answer Read the run and look at the `Unjudged` line: ```bash theme={null} langwatch instant-eval status ``` ``` Unjudged: 12 failed, 3 skipped ``` Pass `--status skipped` or `--status failed` to `results` to read those rows. To judge them, run your own statement over those trace ids. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.