# Why Metrics

Metrics is experiment tracking for research where agents write, launch and read
most of the runs. Logging stays one line of Python, and everything that was
logged can be read back as JSON, SQL or Python objects without a browser. The
app is still there for the moment a person wants to look.

## What changes when agents run the research

A person reading a dashboard skims a hundred curves and remembers which one
looked odd. An agent can't skim a picture it never fetched, and it can't click
through a UI built for a mouse. It needs the same numbers the charts show, in a
form it can parse, filter and compare, reachable from a shell on the machine
where it works.

Agents also run more experiments than people do, in parallel, and in
long-running loops. Tracking has to stay out of the training step, never lose a
point quietly, and make the run's configuration and outcome as easy to query as
its curves.

## What Metrics does

- **Logs from Python with one line per metric.** The [collector](https://metrics.041.io/docs/collector.md)
  queues each value in about eleven microseconds and delivers it from a Rust
  core on its own thread, so training never waits on the network. One
  `flush_or_raise()` at the end fails the job if a single point was lost.
- **Answers every question as JSON.** The [command line](https://metrics.041.io/docs/cli.md) addresses
  experiments by slug and folders by path, prints newline-delimited JSON and
  exits with status 1 on errors. It can also render a chart as a PNG for an
  agent that reads images.
- **Treats runs as a database.** The [DuckDB extension](https://metrics.041.io/docs/duckdb.md) attaches
  folders, experiments, annotations and series as tables with a local Parquet
  cache. The [Python API client](https://metrics.041.io/docs/python-client.md) reads the same data from
  analysis scripts.
- **Keeps every point.** Series are stored at full resolution in a
  [series database of our own](https://metrics.041.io/docs/series-storage.md). Nothing is sampled or
  averaged on the way in.
- **Puts the charts first in the app.** The [app](https://metrics.041.io/docs/app.md) opens on the loss,
  draws every other metric below it and saves the setup as a view the team can
  open.
- **Documents itself for agents.** Every page of these docs is markdown at
  `/docs/<page>.md`, any page answers curl with markdown, and `/llms.txt` lists
  them all. See [working as an agent](https://metrics.041.io/docs/agents.md).

## What we left out

- **Artifacts and checkpoints.** Store them where they already live and put the
  path in an annotation.
- **System monitoring.** Log the GPU numbers you need as metrics; nothing is
  collected behind your back.
- **Hyperparameter search.** Your agent or your sweep tool decides what to run;
  Metrics records what happened.
- **Media and tables.** A metric is a number at a step. Annotations carry text
  and JSON for everything else.

## Price

Free, with fair use. If you need more, or something we don't do yet, email
info@041.io. See [limits and fair use](https://metrics.041.io/docs/limits.md).

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Metrics by 041 documentation. Every page: https://metrics.041.io/llms.txt