Docent Ar

docent-ar — the architecture-review film

You are running the entire docent cascade in architecture-review mode against a repository the user named: survey → treatment → spec → tts → clips → render → open. The output is one MP4 that explains the system the way a distinguished engineer would: the components, the flow, the idioms, the failure modes, the trade-offs, with a verdict.

Arguments

/docent-ar [--subsystem X] [--id X] [--scale S] [--no-open]

• ` — a local repo path, a GitHub URL, or the bare owner/name`

form.

• --subsystem X — scope the review to one subsystem. The survey

resolves this to a concrete code boundary (a directory, a package, a set of files) before starting.

• --id X — override the auto-derived film id (default: ``).
• --scale S — render scale. Default 1. Pass 0.5 for fast

turnarounds.

• --no-open — render without opening the result in the system player.

What to do

1. Pre-flight. Confirm bun, ffmpeg, and the agent CLI are on

PATH. If anything obvious is missing, suggest /docent-doctor and stop.

1. Survey — architecture mode:

``bash bun packages/agent/scripts/survey.ts --mode ar [--subsystem X] [--id X] ``

The survey lands at analysis/.md. When a subsystem is named, section 0 of the survey template resolves it to concrete files first — surface that boundary to the user before moving on. The survey's job here is to interrogate the system: not a tour that admires it, but a depth-first reading that names the trade-off and the failure mode.

Before moving on, surface the lineage sections to the user:

• § 1.5 The premise — one paragraph: the bet this system makes

about the world.

• § 1.6 The novelty — one sentence: the line this system draws

somewhere a prior system did not.

• § 1.7 Prior and similar works — the 2-4 named, dated systems

the film will compare against and the dimension on which each diverges. Confirm with the user that the named lineage is the right lineage before moving on — the rest of the cascade reads from it.

1. Commit to a style. Before the treatment, decide the visual

register the film renders in:

``bash bun run docent style recommend ``

For architecture-review films the recommender will return engineering when the subject is a code repository (most ARs) and paper when the subject is a research-shaped artefact. Take the recommendation unless the survey surfaces a specific reason to override. Surface the choice in one line — "rendering in engineering — system-level architecture review; rationale: ..." — and move on. The spec compilation reads this off the survey's "Style commitment" section and pins it as the spec's style: {preset, intent, rationale} field. The depth-review judge fails the style-committed dimension if the spec ships without it.

3b. Commit to a scene set. Same shape as the style commitment, one layer down — the cognitive moves the film will make.

``bash bun run docent scene-fit recommend ``

The recommender reads the survey and prints the top scene types with rationales tying each to a specific survey finding. Architecture films almost always want prior-art (the lineage from § 1.7), structure (the components), and either tension (the trade-off the design made) or causal-loop / mechanism (when the dynamics matter more than the layout). If the recommender returns warningOnDefault: true, the survey collapsed to the default rut — re-read § 1.5/1.6 and ask whether the system's bet is genuinely about components or about something specific (feedback dynamics → causal-loop; a working motion → mechanism; a regional topology → map). Pin the chosen scene set in the survey's "Scene-set commitment" section.

1. Treatment.

``bash bun packages/agent/scripts/treatment.ts ``

Writes treatments/.md. Print the Angle line so the user sees the through-line you committed to.

1. Spec — and interrogate it.

``bash bun packages/agent/scripts/treatment.ts --to-spec bun packages/agent/scripts/flywheel.ts --max-rounds 2 ``

The first compiles the treatment into films/.json. The second is mandatory — review runs the adversarial judge → revise → re-judge loop bounded to two rounds. On the corpus this reliably lifts a first-draft spec by ~7 points / 30 — the difference between an architecture film that passes the depth contract and one that does not. Surface the verdict score and the weakest dimension (often trade-off, the-numbers, or novelty-named / prior-art-honest for AR films) before rendering. If review exhausts its round budget, stop and ask — do not ship a film the judge rejected.

Before rendering, surface the Prior Art table and the novelty dimension to the user. Open films/.json, find the type: 'prior-art' scene, and tell the user, in one line:

> "This film argues that <subject>'s novelty is > <dimension label>: <novelty.statement>. The lineage: > <system labels>. Confirm before render."

Wait for confirmation. A user who pushes back on the novelty dimension is steering the film's spine — do not render past their objection.

1. Render.

``bash bun run docent build --scale 1 ``

1. Open the result (unless --no-open). On macOS: open out/.mp4.

1. Hand back. Three things to the user:

• the film id (so they can re-render via /docent-build ),
• the verdict score,
• one sentence naming the trade-off the film adjudicates.

Knowing when to stop and ask

Pause and ask the user instead when:

• The repo is too large to cover at depth and no subsystem was named.

Surface a candidate list of 2–4 subsystems with one-line summaries; let the user pick.

• The survey surfaces two equally plausible angles (a control-plane vs.

data-plane reading, a present vs. historical reading) — let the user pick the one the film should commit to.

• review exhausts its round budget without passing the depth contract.

Surface the failing dimensions; do not silently ship a film the judge rejected.

Failure modes

• Repo not local — survey --mode ar clones the repo when given a

URL. If the clone fails (auth, network), surface the failure and stop.

• Agent CLI missing — survey and treatment shell out to claude

or codex. If neither is on PATH, suggest /docent-doctor.

• **The judge keeps failing the trade-off dimension** — the survey

named components and flow but did not name what the system gives up by being what it is. Ask the user what the load-bearing trade-off is, or drop back to /docent-survey --mode ar and steer the analysis directly.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: benelser
• Source: benelser/docent
• License: MIT
• Homepage: https://github.com/benelser/docent

Install and usage instructions live in the source repository linked above.