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/marimo-team/skills/implement-paper-autonpx skills add marimo-team/skills --skill implement-paper-autogit clone --depth 1 https://github.com/marimo-team/skillsWrote 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/marimo-team/skills/implement-paper-auto)<a href="https://agentmods.dev/skills/marimo-team/skills/implement-paper-auto"><img src="https://agentmods.dev/badge/skills/marimo-team/skills/implement-paper-auto.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.00963 |
| Opus 5 | $0.00010 | $0.00481 |
| Sonnet 5 | $0.00004 | $0.00193 |
| Haiku 4.5 | $0.00002 | $0.00096 |
Grade A, and why
implement-paper-auto 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://alphaxiv.org/overview/{PAPER_ID}.md" This is a copy
98% identical to auto-paper-demo — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You need to come up with a compelling story to tell from a paper. Do not ask the user for feedback/input. You need to apply thinking and come up with the best story yourself.
Fetching Papers via AlphaXiv
Use alphaxiv.org to get structured, LLM-friendly paper content. This is faster and more reliable than trying to read a raw PDF.
Extract the paper ID
Parse the paper ID from whatever the user provides:
| Input | Paper ID |
|---|---|
https://arxiv.org/abs/2401.12345 |
2401.12345 |
https://arxiv.org/pdf/2401.12345 |
2401.12345 |
https://alphaxiv.org/overview/2401.12345 |
2401.12345 |
2401.12345v2 |
2401.12345v2 |
2401.12345 |
2401.12345 |
Fetch the AI-generated overview (try this first)
curl -s "https://alphaxiv.org/overview/{PAPER_ID}.md"
Returns a structured, detailed analysis of the paper as plain markdown. One call, no JSON parsing.
Fetch the full paper text (fallback)
If the overview doesn't contain the specific detail you need (e.g., a particular equation, table, or proof):
curl -s "https://alphaxiv.org/abs/{PAPER_ID}.md"
Returns the full extracted text of the paper as markdown.
Error handling
- 404 on the overview: Report hasn't been generated for this paper yet. Try the full text instead.
- 404 on the full text: Text hasn't been processed yet. As a last resort, direct the user to the PDF at
https://arxiv.org/pdf/{PAPER_ID}. - No authentication is required — these are public endpoints.
What is a good implementation?
A good implementation tells a story, that's the most important thing. The story should be simple, but it should not be missing.
Papers typically have more than one concept in them. So that means you need to pick a story! It isn't the goal to fully implement the paper or to rerun a giant benchmark. The goal is to take a lesson/idea and to explain that very clearly in a notebook that can simply run on a CPU. That way, a user can easily run learn something from it. When you look at the notebook, what is the main concept or idea that you think is worth exploring? What is the concept that tells a story?
What ships with it
1 file 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.
- 5d ago First seen · 73 lines · 20 tokens per session scan A 8c4e8570d8e4
implement-paper-auto is a skill published in the GitHub repository marimo-team/skills (172 stars, last pushed 16d ago), licensed Apache-2.0. It adds 20 tokens to every session and 963 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 98% identical to auto-paper-demo, differing in 4 lines, and is treated as a copy.
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