> For the complete documentation index, see [llms.txt](https://docs.openmind.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.openmind.com/observability/tracer.md).

# Tracer & Quality Scorer

### Overview

OM1 includes an **execution tracer** that records what the runtime does each turn, and an optional **quality scorer** that evaluates the agent's responses as it runs.

* The **tracer** (`internal/tracer`) writes structured trace events to disk.
* The **quality scorer** subscribes to those trace events and scores each turn for coherence, input classification, and language, exporting the results as Prometheus metrics.

Both are off by default and enabled through the `use_tracer` config block.

### Configuration

```json5
use_tracer: {
  enabled: true,
  quality_scorer: {
    enabled: true,
  },
},
```

| Field                               | Type | Default | Description                                                            |
| ----------------------------------- | ---- | ------- | ---------------------------------------------------------------------- |
| `use_tracer.enabled`                | bool | `false` | Turns the execution tracer on.                                         |
| `use_tracer.quality_scorer.enabled` | bool | `false` | Turns the live quality scorer on. Requires `use_tracer.enabled: true`. |

> **Note:** If `quality_scorer.enabled` is `true` but `use_tracer.enabled` is `false`, the quality scorer will **not** start (the tracer logs a warning). The scorer depends on the trace event stream.

### Trace output

When enabled, the tracer writes newline-delimited JSON to the `traces/` directory, rotating the file daily:

```
traces/tracer_<YYYY-MM-DD>.jsonl
```

Each line is one trace event from a turn of the core loop.

### Quality scoring

With the quality scorer enabled, each turn is evaluated along three dimensions:

* **Coherence** — is the response coherent with the prompt? (`coherent` / `marginal` / `incoherent`, also mapped to a numeric score of `1` / `0.5` / `0`).
* **Input classification** — how the user input was handled (`positive` / `marginal` / `negative` / `not_addressed`).
* **Language** — the detected spoken language of the turn.

The scores are exported as the `om1_quality_live_*` Prometheus metrics, so you can build a Grafana panel showing response quality trending in real time alongside the latency metrics. See the [Metrics Reference](/observability/metrics.md#response-quality-live-quality-scorer) for the exact metric names and types.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.openmind.com/observability/tracer.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.