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.
npx agentmods add instructions/dev-the-dev-while-deving/rolldeep-lab/agents-mdgit clone --depth 1 https://github.com/dev-the-dev-while-deving/rolldeep-labWhat 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.
| Model | Per session | Once 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 |
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.
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
- User drops a syllabus into
content/syllabi/. - You read it, break it into 25–60 minute units, write
content/units/<name>.json. - 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. - User studies however they want and makes a video so they actually did it.
- 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.
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.
- yesterday First seen · 61 lines · 512 tokens per session scan A 049274306c54
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.
Other instructions, from other repositories
learndeck AGENTS.md
AGENTS.md instructions for learn-deck/learndeck, covering learndeck agent instructions, when a learner says “let's start”, teaching and safety boundary and course authoring.
jupyter-mcp-server copilot-instructions.md
Instructions for datalayer/jupyter-mcp-server, covering jupyter mcp server, working effectively, environment setup, build and install (critical: network limitations) and standard installation (may fail with network issues).
gini-agent AGENTS.md
AGENTS.md instructions for Open-Curiosity/gini-agent, covering gini agent instructions, shape, adrs, boundaries and branches.
barkeep AGENTS.md
Instructions for iannuttall/barkeep, covering agent notes, product rules, repo map, commands and app structure.
blz AGENTS.md
Instructions for outfitter-dev/blz, covering blz repository instructions for ai agents, important, working memory, use blz and 🚀 quick start for agents.
rondoflow CLAUDE.md
Instructions for rondoflow/rondoflow, covering rondoflow, project overview, tech stack, development and setup.