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 skills/wolfpackofone/q-agent/marimo-pairnpx skills add WolfpackOfOne/Q-agent --skill marimo-pairgit clone --depth 1 https://github.com/WolfpackOfOne/Q-agentWhat 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 | $0.00049 | $0.03785 |
| Opus 5 | $0.00024 | $0.01893 |
| Sonnet 5 | $0.00010 | $0.00757 |
| Haiku 4.5 | $0.00005 | $0.00379 |
Grade B, and why
marimo-pair scanned grade B with 1 finding 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 2d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
`~/.claude/settings.json` (global): How it starts
The opening of the file, as written. The whole thing — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.
marimo Pair Programming Protocol
This skill gives you full access to a running marimo notebook. You can read cell code, create and edit cells, install packages, run cells, and inspect the reactive graph — all programmatically. The user sees results live in their browser while you work through bundled scripts or MCP.
Philosophy
marimo notebooks are a dataflow graph — cells are the fundamental unit of computation, connected by the variables they define and reference. When a cell runs, marimo automatically re-executes downstream cells. You have full access to the running notebook.
- Cells are your main lever. Use them to break up work and choose how and when to bring the human into the loop. Not every cell needs rich output — sometimes the object itself is enough, sometimes a summary is better. Match the presentation to the intent.
- Understand intent first. When clear, act. When ambiguous, clarify.
- Follow existing signal. Check imports,
pyproject.toml, existing cells, anddir(ctx)before reaching for external tools. - Stay focused. Build first, polish later — cell names, layout, and styling can wait.
Prerequisites
How to invoke marimo
Only servers started with --no-token register in the local server registry
and are auto-discoverable — starting without a token makes discovery easier.
If a server has a token, set the MARIMO_TOKEN environment variable before
calling the execute script (avoids leaking the token in process listings). The
right way to invoke marimo depends on context (project
tooling, global install, sandbox mode). See
finding-marimo.md for the full decision tree.
Do NOT use --headless unless the user asks for it. Omitting it lets
marimo auto-open the browser, which is the expected pairing experience. If the
user explicitly requests headless, offer to open http://localhost:<port>
in their browser (open on macOS, xdg-open on Linux, start on Windows).
Troubleshooting
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 348 lines · 49 tokens per session scan B 0665418ec92f
marimo-pair is a skill published in the GitHub repository WolfpackOfOne/Q-agent (5 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 3,785 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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