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 Lord1Egypt/scientific-agent-toolkit --skill paper-lookupgit clone --depth 1 https://github.com/Lord1Egypt/scientific-agent-toolkitWrote 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/lord1egypt/scientific-agent-toolkit/paper-lookup)<a href="https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/paper-lookup"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/paper-lookup/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/lord1egypt/scientific-agent-toolkit/paper-lookup"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/paper-lookup.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 | $0.00122 | $0.02492 |
| Opus 5 | $0.00061 | $0.01246 |
| Sonnet 5 | $0.00024 | $0.00498 |
| Haiku 4.5 | $0.00012 | $0.00249 |
Grade A, and why
paper-lookup 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 8d 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.
| Claude Code | `WebFetch` | `curl` via Bash | This is a copy
98% identical to paper-lookup — 2 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 — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Lookup
You have access to 10 academic paper databases through their REST APIs. Your job is to figure out which database(s) best serve the user's query, call them, and return the results.
Core Workflow
-
Understand the query -- What is the user looking for? A specific paper by DOI? Papers on a topic? An author's publications? Open access PDFs? Full text? This determines which database(s) to hit.
-
Select database(s) -- Use the database selection guide below. Many queries benefit from hitting multiple databases -- for example, searching PubMed for papers and then checking Unpaywall for open access copies.
-
Read the reference file -- Each database has a reference file in
references/with endpoint details, query formats, and example calls. Read the relevant file(s) before making API calls. -
Make the API call(s) -- See the Making API Calls section below for which HTTP fetch tool to use on your platform.
-
Return results -- Always return:
- The raw JSON (or parsed XML for arXiv) response from each database
- A list of databases queried with the specific endpoints used
- If a query returned no results, say so explicitly rather than omitting it
Database Selection Guide
Match the user's intent to the right database(s).
By Use Case
| User is asking about... | Primary database(s) | Also consider |
|---|---|---|
| Papers on a biomedical topic | PubMed | Semantic Scholar, OpenAlex |
| Full text of a biomedical article | PMC | CORE |
| Biology preprints | bioRxiv | Semantic Scholar, OpenAlex |
| Health/medical preprints | medRxiv | Semantic Scholar, OpenAlex |
| Physics, math, or CS preprints | arXiv | Semantic Scholar, OpenAlex |
| Papers across all fields | OpenAlex | Semantic Scholar, Crossref |
| A specific paper by DOI | Crossref | Unpaywall, Semantic Scholar |
| Open access PDF for a paper | Unpaywall | CORE, PMC |
| Citation graph (who cites whom) | Semantic Scholar | OpenAlex |
| Author's publications | Semantic Scholar | OpenAlex |
| Paper recommendations | Semantic Scholar | -- |
| Full text (any field) | CORE | PMC (biomedical only) |
| Journal/publisher metadata | Crossref | OpenAlex |
| Funder information | Crossref | OpenAlex |
| Convert between PMID/PMCID/DOI | PMC (ID Converter) | Crossref |
| Recent preprints by date | bioRxiv, medRxiv | arXiv |
What ships with it
10 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.
- 8d ago First seen · 194 lines · 122 tokens per session scan A d61270ca9b31
paper-lookup is a skill published in the GitHub repository Lord1Egypt/scientific-agent-toolkit (3 stars, last pushed 3mo ago), licensed MIT. It adds 122 tokens to every session and 2,492 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 98% identical to paper-lookup, differing in 2 lines, and is treated as a copy.
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