Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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 K-Dense-AI/scientific-agent-skills --skill paperzillagit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-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/k-dense-ai/scientific-agent-skills/paperzilla)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/paperzilla"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/paperzilla/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/k-dense-ai/scientific-agent-skills/paperzilla"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/paperzilla.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00047 | $0.00926 |
| Opus 5 | $0.00023 | $0.00463 |
| Sonnet 5 | $0.00009 | $0.00185 |
| Haiku 4.5 | $0.00005 | $0.00093 |
Grade A, and why
paperzilla 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 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.
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.
Copies of this mod
4 near-identical copies found in the catalogue:
- paperzilla — 100% identical, 2 lines differ
- paperzilla — 100% identical, 4 lines differ
- paperzilla — 97% identical, 3 lines differ
- paperzilla — 97% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paperzilla
Use this skill when you want to chat with your agent about projects, recommendations, and canonical papers in Paperzilla.
What you can ask
- "Give me the latest recommendations from project X."
- "Open recommendation Y and explain why it matters."
- "Fetch canonical paper Z as markdown and summarize it."
- "Tell me how this paper is relevant to my research."
- "Show me the feed for project X."
- "Leave feedback on a recommendation."
- "Export this paper, recommendation, or feed as JSON."
This is the core Paperzilla skill. It gives your agent direct access to Paperzilla data, but it does not impose a workflow or external delivery integration.
Access method
Most current profiles in this repo use the pz CLI.
If the current profile ships extra agent-specific instructions, follow those as well.
Install
macOS
brew install paperzilla-ai/tap/pz
Windows (Scoop)
scoop bucket add paperzilla-ai https://github.com/paperzilla-ai/scoop-bucket
scoop install pz
Linux
Use the official Linux install guide:
Build from source (Go 1.23+)
See the CLI repository for source builds:
Update
Check whether your CLI is up to date and get install-specific upgrade steps:
pz update
If detection is ambiguous, override it explicitly:
pz update --install-method homebrew
pz update --install-method scoop
pz update --install-method release
pz update --install-method source
Supported values are auto, homebrew, scoop, release, and source.
Authentication
pz login
CLI reference
If the current profile uses pz, these are the core commands.
List projects
pz project list
Show one project
pz project <project-id>
Browse project feed
pz feed <project-id>
Useful flags:
--must-read--since YYYY-MM-DD--limit N--json--atom
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 · 160 lines · 47 tokens per session scan A 02d956fb9442
paperzilla is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,220 stars, last pushed 4d ago), licensed MIT. It adds 47 tokens to every session and 926 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
Other skills, from other repositories
discovery-toolbox
A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…
discovery-director
Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…
polars-dovmed
Search PMC Open Access and bioRxiv corpora with polars-dovmed. Use when structured, reproducible literature queries should run through the hosted API or local parquet indexes.
bio-interdomain-hgt
Detect and polarize interdomain horizontal gene transfer with homology, context, and phylogenetic checks. Use when studying lateral gene transfer, virus-host gene exchange, endogenous viral elements, or donor direction.
csag-extraction
Extract a Conditional Scientific Argumentation Graph and grounded Q&A from a manuscript. Use when representing assertions, contexts, evidence links, and inference steps in machine-readable form.
exploratory-data-analysis
Inspect scientific data and generate a Markdown structure-and-quality report. Use when triaging tabular, array, sequence, HDF5, JSON, or raster files before downstream analysis.