docent-ar

docent-ar is a skill for Claude Code, Codex from benelser/docent. It costs 90 tokens per session (1,899 once invoked), scanned A, original, MIT.

A tool that turns an architecture review into a narrated video. Software architecture is the system’s parts, connections, data flow, and design decisions.

In plain words
What is it for?
Use it to review an entire repository or a named subsystem, covering components, control and data flow, design patterns, failure modes, and an overall verdict.
Why use it?
It gives teams a visual explanation of how a system works, where it can fail, and what trade-offs its design makes.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/benelser/docent/docent-ar
Any agent
npx skills add benelser/docent --skill docent-ar
Clone the repo
git clone --depth 1 https://github.com/benelser/docent

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for docent-ar

README.md
[![agentmods](https://agentmods.dev/badge/skills/benelser/docent/docent-ar.svg)](https://agentmods.dev/skills/benelser/docent/docent-ar)
Your own site
<a href="https://agentmods.dev/skills/benelser/docent/docent-ar"><img src="https://agentmods.dev/badge/skills/benelser/docent/docent-ar.svg" alt="Measured on agentmods" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,899 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00090 $0.01899
Opus 5 $0.00045 $0.00949
Sonnet 5 $0.00018 $0.00380
Haiku 4.5 $0.00009 $0.00190

Measured 4d ago against content hash ae8913ffdf8b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

docent-ar scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/agent/skills/docent-ar/SKILL.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 <repo> [--subsystem X] [--id X] [--scale S] [--no-open]

  • <repo> — 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: <repo-name>).
  • --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.

  2. Survey — architecture mode:

    bun packages/agent/scripts/survey.ts <repo> --mode ar [--subsystem X] [--id X]
    

    The survey lands at analysis/<id>.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.

Read the full file on GitHub · 177 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 177 lines · 90 tokens per session scan A ae8913ffdf8b

Subscribe to this mod's changes

docent-ar is a skill published in the GitHub repository benelser/docent (6 stars, last pushed 2mo ago), licensed MIT. It adds 90 tokens to every session and 1,899 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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