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 skills add fmind/dot --skill marimogit clone --depth 1 https://github.com/fmind/dotWrote 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.
[](https://agentmods.dev/skills/fmind/dot/marimo)<a href="https://agentmods.dev/skills/fmind/dot/marimo"><img src="https://agentmods.dev/badge/skills/fmind/dot/marimo/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/fmind/dot/marimo"><img src="https://agentmods.dev/badge/skills/fmind/dot/marimo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.01017 |
| Opus 5 | $0.00020 | $0.00508 |
| Sonnet 5 | $0.00008 | $0.00203 |
| Haiku 4.5 | $0.00004 | $0.00102 |
Grade A, and why
marimo scanned grade A 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Pairing scripts require `bash`, `curl`, and `jq` plus authority to execute code in the selected notebook. Review scripts and any harness permission entries through the [vendor-skill policy](../agent-project/references/ve How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
marimo
Use marimo for reactive Python notebooks and apps; configure agent pairing and harness workflows, and install upstream skills through agent-project.
Workflow
- Inspect the environment: use
marimo --versionand the installed command help; preferuv run marimowhen the project declares marimo. Preserve the notebook's dependency model, including existing PEP 723 metadata. - Edit with disk reload:
marimo edit --watch notebook.pylets the running notebook reload agent edits. Keep the default loopback host and token authentication; cell execution can access local files, network services, and credentials. - Respect reactivity: each global name belongs to one cell; use
_namefor cell-local intermediates. Preserve@app.cellstructure and make side effects deliberate because dependent cells can rerun after upstream edits. - Check before fixing:
marimo check --strict notebook.pyreports notebook diagnostics and fails on warnings. Applymarimo check --fix notebook.pyonly to the intended file, review the diff, then rerun the strict check. Fixes do not automatically repair every dependency or syntax problem;--unsafe-fixescan change behavior. - Exercise behavior: run representative inputs and inspect outputs and exceptions in the notebook. Lint success alone does not prove cell execution, data correctness, or app behavior.
- Convert or export: use the commands below, review conversion diagnostics, and validate the result. HTML export executes the notebook unless an installed option says otherwise; outputs and source may contain private data.
marimo runhides editing controls but still executes Python on the server.
Commands
marimo edit --watch notebook.py
marimo check --strict notebook.py
marimo run notebook.py
marimo convert notebook.ipynb -o notebook.py
marimo export html notebook.py -o notebook.html
marimo pair prompt --url http://127.0.0.1:2718 --with-token
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.
- today Changed · +1 lines 8e3d31d9e6fd
- 2d ago First seen · 52 lines · 41 tokens per session scan A 34a9379fccc5
marimo is a skill published in the GitHub repository fmind/dot (4 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 1,017 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-10.
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