---
title: "command-school-corpus — Mova code model"
description: "Mova code model of tools/octopus/src/commands.rs: components with their labels, obernants and the model text."
url: "https://groupants.elamur.ai/free/en/mova/tools/octopus/src/commands.rs.groupant/"
---
Elamur: [Mova](https://md.mova.elamur.ai/free/en/) · [Dictionary](https://md.dictionary.elamur.ai/free/en/) · [Research](https://md.research.elamur.ai/free/en/) · **Groupants**

This page as HTML: <https://groupants.elamur.ai/free/en/mova/tools/octopus/src/commands.rs.groupant/>

# command-school-corpus

The groupant beside tools/octopus/src/commands.rs in the Mova repository: what the code computes, what it never does, how to go back from its outputs, its invariants, cost and checks.

## Facts

- **kind:** groupant
- **status:** partial source bound model
- **source:** [`tools/octopus/src/commands.rs`](https://github.com/ElamurAI/mova-free/blob/main/tools/octopus/src/commands.rs)
- **source SHA-256:** `4d497a0032961592…`
- **repository folder:** [`tools/octopus/src/commands.rs.groupant`](https://github.com/ElamurAI/mova-free/tree/main/tools/octopus/src/commands.rs.groupant)
- **repository commit:** `48f2e6f74146`

> **Implementation material.** A Mova code model describes this code at one source revision: partial models, finite checks and their stated scope. It is not a reviewed general exposition, and its labels are shown as written, never raised.

## Components

| component | label | where |
|---|---|---|
| **approximant** | partial source derived | [Forward](#forward) |
| **ast** | partial | `syntax.json` |
| **composition** | partial source derived | [Composition](#composition) |
| **cost** | partial source derived | [Cost](#cost) |
| **descriptant** | partial source derived | [Descriptant](#descriptant) |
| **invariant** | partial source derived | [Invariant](#invariant) |
| **tests** | finite native checks | [checks](#checks) |

## Obernants

The typed relations around the forward model: the behaviour complement (what the code never does), the reverse reconstruction (every input compatible with an output) and specialised views.

| id | type | label | where |
|---|---|---|---|
| `behavior_complement` | behavior_complement | source derived finite checked | [behavior_complement](#behavior-complement) |
| `reverse_reconstruction` | reverse_reconstruction | source derived finite checked | [reverse_reconstruction](#reverse-reconstruction) |

## Model text


### model

## Command school corpus and exam — source-bound model

### Descriptant

`commands.rs` is the start of the command school: an anonymized corpus of commands sent to Crab and an exam that
replays reviewed commands through Mova's understanding in plan mode (nothing executed). As in the primary school, a
command an arbitrary Mova-based animal does not understand signals a gap in the learning algorithm, not data to
memorize. Lessons and a command dictionary follow the primary-school pipeline later.

### Forward

anonymize: whitespace tokens whose punctuation-trimmed core is an absolute or home path → `<path>`, contains `://` →
`<url>`, looks like an e-mail → `<email>`, is a ≥12-char hex/dash run with ≥4 digits or a ≥5-digit number → `<id>`;
everything else (words, role names, small numbers) unchanged. record: append `{text, priority, observed, origin}`
(JSONL, 0600). exam: for each entry with `expected`, compare `reading(review(text))` (plan capabilities in order, or
refusal stage) and count by kind; unreviewed entries are only counted.

### Invariant

anonymize is idempotent; the exam never executes a capability (it calls review only); observed readings never become
expectations automatically — `expected` is written by review.

### Cost

Linear in prompt length for anonymize; one native parse per examined entry.

### Composition

The `crab` binary records every ask (optional corpus path on `serve`) and exposes `crab exam` and `crab audit`.

### behavior_complement

Not anonymized: names of people or organisations written as plain words, short numbers, relative paths; the audit only
checks idempotence of these rules, not semantic privacy. Not done: lesson generation, dictionary, training.

### reverse_reconstruction

From an anonymized text the original paths, ids, e-mails and URLs are not recoverable (many-to-one); the reading
recovers which configured capability or refusal stage the understanding produced, not the execution outcome.

### Epoch 2026-11-04: Executed failures, review loop and generated exercises

`Reading::ExecutedFailed{capabilities}` marks an understood plan whose execution failed; it is never examined as a refusal and cannot be a reviewed expectation. `review_queue` lists observed texts without a reviewed expectation; `promote` admits reviewer decisions only when observed, privacy_review=passed, anonymized, a reading (plan/refusal) and not yet reviewed — never training. `exercises` derives determiner variants and same-shaped other-entity variants (same handler and parameters except the target; a headed name only within its configured group) from reviewed single-capability plans. `group_candidates` groups legacy and deduplicated review files read-only.

### checks

#### Checks (2026-11-03)

anonymize keeps English and hides path/id/e-mail/URL, idempotent; audit refuses raw paths. Live: 21 reviewed seed commands examined twice with identical output, 21/21 after correcting one refusal-stage expectation.

2026-11-04: unit tests for determiner toggling, promote gate (privacy, observation, execution outcome, duplicates), review queue and exercises with a negative control; live: seed 52/53 (the one failure is a reviewed refusal now understood: "Is the documenter running?"), 123 generated exercises from the seed all pass.