rolldeep-lab AGENTS.md

Repository instructions for working on RollDeep Lab, a local study workspace. They explain which syllabus and study-unit files to edit, how runtime data is stored, and which commands control the lab.

In plain words
What is it for?
Use them when adding syllabus units, syncing content, running the lab, changing its product code, or using commands for study status, topic selection, rolling, and completion.
Why use it?
They reduce uncertainty about where study content belongs and how changes are synchronised. They also document the expected JSON shape for study units and the development workflow.

Instructions file for CodexOpenCode

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 instructions/dev-the-dev-while-deving/rolldeep-lab/agents-md
Clone the repo
git clone --depth 1 https://github.com/dev-the-dev-while-deving/rolldeep-lab

Made for: Codex, OpenCode.

Per session 512 This file is loaded in full into every session.
When invoked 512 The same file — it is already loaded in full.
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 $0.00512 $0.00512
Opus 5 $0.00256 $0.00256
Sonnet 5 $0.00102 $0.00102
Haiku 4.5 $0.00051 $0.00051

Measured yesterday against content hash 049274306c54, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rolldeep-lab AGENTS.md 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 yesterday.

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.

AGENTS.md · 61 lines

What it actually says

RollDeep — how the agent works this lab

You are the backend. The browser is just the roll surface.

Files you edit

Path What
content/syllabi/* Raw syllabus drops (markdown/text). Read these.
content/units/*.json The pool. You write these. One file per syllabus.
app/lib/cli/mcp Product code. Change it when the lab needs to behave differently.

SQLite in ~/.rolldeep/ is runtime state (rolls, streak, completions). Do not treat it as the source of the pool.

Unit file shape:

{
  "title": "Source name",
  "units": [
    {
      "title": "Small enough for 25–60 min of depth",
      "question": "One sharp curiosity itch. Never 'What is X?'",
      "minutes": 40,
      "stars": 3,
      "sourceExcerpt": "where this came from"
    }
  ]
}

After writing unit files: they sync on Lab page load, or npm run rd -- sync.

Commands

npm run lab                 # http://127.0.0.1:3210
npm run rd -- syllabi
npm run rd -- use --title "Course name"
npm run rd -- status
npm run rd -- roll
npm run rd -- choose --id <id>
npm run rd -- complete --id <id> --url https://... --notes "..."
npm run rd -- sync
npm run rd -- reset

Workflow

  1. User drops a syllabus into content/syllabi/.
  2. You read it, break it into 25–60 minute units, write content/units/<name>.json.
  3. Sync. User picks a syllabus in the dropdown (or rolldeep use). Hits ROLL (max 5 per session on that syllabus). They can see the current roll plus 3 previous and TAKE one.
  4. User studies however they want and makes a video so they actually did it.
  5. They mark completed with that proof. That title never rolls again on that syllabus. Other syllabi keep their own completion.

Hardness is 1–5 stars on each unit.

No study templates. No filming scripts. Proof is required to complete.

Do not call xAI to mint units. You author them.

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. yesterday First seen · 61 lines · 512 tokens per session scan A 049274306c54

Subscribe to this mod's changes

rolldeep-lab AGENTS.md is an instructions file published in the GitHub repository dev-the-dev-while-deving/rolldeep-lab (0 stars, last pushed 11d ago), licensed MIT. It adds 512 tokens to every session, about $0.0026 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.