> ## Documentation Index > Fetch the complete documentation index at: https://docs.trymonte.ai/llms.txt > Use this file to discover all available pages before exploring further. # Environment > The graded task package a Measurement freezes An Environment is the graded world: the tasks, their gold answers, and the grader that scores an attempt. It is delivered as an installable Python package. Installing the package is what makes its name available to `monte init`. ## Tasks A Task is one question with its gold answer. It is the unit a Split enumerates, the grader scores, and rollouts run against. A Task belongs to the Environment and is identical for every Run. ## Anatomy An Environment implements a small protocol: * `splits()` names its task-ID lists. * `grade(task, output)` returns a score, under a declared grader identity. * `fingerprint()` hashes the task source, the grader, and the harness config. * `install()` and `verify_install()`, both optional, set up and check box assets. Discovery runs through the `monte.environments` entry point. The box bootstrap never knows an Environment by name: `monte env install --all` installs whatever is registered. ## The grader The grader is the non-negotiable part. Ungraded data is never an input to the platform. One grader serves eval, training, and spot-checks, so scores cannot drift apart by construction. ## Available Environments | Name | Kind | Purpose | | ------ | --------- | ------------------------------------------------------------ | | `demo` | mock-only | exercises the loop itself, no real data | | `math` | real | graded math tasks, frozen Splits verified against a manifest | The `math` Splits live on the durable data root, not in the repo. They are seeded by a manifest-verified copy and never derived on a box. ## Related pages Build one: package shape, rules, and how to test it. How an Environment gets frozen into something measurable.