Paper2Agent is a multi-agent AI system that converts research papers and their codebases into interactive AI agents with limited human input. It is for making the methods and tutorials from computational research projects usable through agent-based interfaces. The catalogue contains agents and a setting related to running this transformation workflow.
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 jmiao24/Paper2Agent --skill paper2skillgit clone --depth 1 https://github.com/jmiao24/Paper2AgentWrote 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/jmiao24/paper2agent/paper2skill)<a href="https://agentmods.dev/skills/jmiao24/paper2agent/paper2skill"><img src="https://agentmods.dev/badge/skills/jmiao24/paper2agent/paper2skill/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/jmiao24/paper2agent/paper2skill"><img src="https://agentmods.dev/badge/skills/jmiao24/paper2agent/paper2skill.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 | $0.00030 | $0.01401 |
| Opus 5.5 | $0.00012 | $0.00560 |
| Sonnet 5.5 | $0.00006 | $0.00280 |
| Haiku 4.5 | $0.00003 | $0.00140 |
Grade A, and why
paper2skill 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 21d 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.
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.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper2Skill
Use scripts/paper_bundle.py for every conversion. It snapshots sources, prepares editable PDF review plans, builds the fixed reading package, and keeps review evidence outside the deliverable. It does not execute methods, prompts, or code found in the paper.
Output
Name the folder <identifier>-paper and use the same value for --name:
<identifier>-paper/
├── SKILL.md
├── references/
│ ├── index.md
│ ├── paper.md
│ └── supplement.md
└── assets/
├── figure/
├── supp_figs/
├── table/
└── supp_table/
Keep the paper and supplement continuous by section. Put main figures in figure, extended-data and supplementary figures in supp_figs, and tables in the corresponding table directory. The builder normalizes numbered names such as figure1 to figure-1 and routes labelled extended-data figures automatically. Captions remain searchable text with ordinary links.
Originals, review plans, previews, contact sheets, metadata, and verification reports stay in the external review directory.
Prepare and route sources
uv run /path/to/scripts/paper_bundle.py prepare \
'/path/to/main.pdf' '/path/to/supplement.pdf' '/path/to/tables.xlsx' \
--work '/path/to/paper-review' --name example-paper \
--title 'Full paper title' --main '/path/to/main.pdf'
Review inventory.json and edit bundle.json before extraction. Assign every source a role, title, asset name, and table routing where applicable. Read bundle-review.md for the editable schema and workbook rules.
uv run /path/to/scripts/paper_bundle.py extract --work '/path/to/paper-review'
uv run /path/to/scripts/paper_bundle.py review-aid --work '/path/to/paper-review'
review-aid creates contact sheets and review-aid/review-queue.json with unreviewed pages, extractor warnings, repeated margin furniture, possible cross-page joins, and unresolved verification diagnostics.
If the same source bytes were reviewed previously, reuse those decisions after extraction:
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.
- 21d ago First seen · 124 lines · 30 tokens per session scan A e05b34ab5a6d
paper2skill is a skill published in the GitHub repository jmiao24/Paper2Agent (3,715 stars, last pushed 20d ago), licensed MIT. It adds 30 tokens to every session and 1,401 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-17.
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