> ## Documentation Index
> Fetch the complete documentation index at: https://runmirrors.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# CLI

> The mirrors command — full parity with the web app, from your terminal.

The `mirrors` CLI is a terminal client of the hosted backend with **full parity with the web app**: anything you can do in the UI you can do from the CLI — log in, ingest and build a twin, explore it, run it, add business context, apply agent-suggested fixes, and author + run evals. It talks only HTTP to the backend; it has no engine or build logic of its own.

## Install

It ships in the Python `mirrorkit` package behind the `cli` extra:

```bash theme={null}
pip install "mirrorkit[cli]"   # adds the `mirrors` command
```

## Log in

Authenticate with a workspace API key (`mk_live_…`, minted in the web app under **Settings → API keys**):

```bash theme={null}
mirrors login    # paste the key (or --api-key / --dev)
```

Credentials live in `~/.mirrors/config.json`. For CI, set `MIRRORS_BASE_URL` / `MIRRORS_API_KEY` instead.

## Commands

```bash theme={null}
mirrors env ls                                 # list environments
mirrors build traces.jsonl --name airline      # ingest + build a twin (streams the log)
mirrors build --project airline --name airline # build from a collector stream

mirrors env assets <env>                       # explore the twin…
mirrors env schema <env>
mirrors env fidelity <env>
mirrors env drift <env>
mirrors env traces <env>

mirrors query <env> "cancel my flight"         # run the twin (one-shot) + see the trace
mirrors chat <env>                             # multi-turn conversation with the twin
mirrors container status|start|stop <env>      # its hosted HTTP endpoint

mirrors context add <env> --text "…"           # business context that lifts fidelity
mirrors proposal new <env>                     # agent-suggested changes…
mirrors proposal accept <env> <id>             # …accept -> rebuild

mirrors eval generate <env> --save-as smoke    # auto-author eval cases
mirrors eval create <env> --name smoke --from cases.json
mirrors eval run <eval-set-id>                 # run evals
mirrors run show <run-id>                      # inspect a run

mirrors usage                                  # task-minutes vs. plan allowance
```

<Tip>
  Add `--json` to any command for machine-readable output — handy in scripts and CI.
</Tip>

## Typical flow

<Steps>
  <Step title="Build">
    `mirrors build --project my-agent --name my-agent` turns collected traces into a runnable twin, streaming the build log.
  </Step>

  <Step title="Explore and query">
    `mirrors env fidelity my-agent` shows per-tool scores; `mirrors query my-agent "…"` runs a session and prints the trace.
  </Step>

  <Step title="Eval">
    `mirrors eval generate my-agent --save-as smoke` auto-authors cases from your traces, then `mirrors eval run <id>` scores the agent against them.
  </Step>
</Steps>