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 pyzoterogit 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/pyzotero)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/pyzotero"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/pyzotero/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/pyzotero"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/pyzotero.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00085 | $0.01716 |
| Opus 5 | $0.00043 | $0.00858 |
| Sonnet 5 | $0.00017 | $0.00343 |
| Haiku 4.5 | $0.00009 | $0.00172 |
Grade A, and why
pyzotero 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 9d 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pyzotero
Pyzotero is a Python wrapper for the Zotero API v3. Use it to programmatically manage Zotero libraries: read items and collections, create and update references, upload attachments, manage tags, and export citations.
Current upstream: pyzotero 1.13.0 (PyPI, May 2026). Docs: pyzotero.readthedocs.io.
Authentication Setup
Required credentials — get from https://www.zotero.org/settings/keys:
- User ID: shown as "Your userID for use in API calls"
- API Key: create at https://www.zotero.org/settings/keys/new
- Library ID: for group libraries, the integer after
/groups/in the group URL
Store credentials in environment variables or a .env file:
ZOTERO_LIBRARY_ID=your_user_id
ZOTERO_API_KEY=your_api_key
ZOTERO_LIBRARY_TYPE=user # or "group"
See references/authentication.md for full setup details.
Installation
uv add pyzotero # Web API client
uv add "pyzotero[cli]" # + local CLI (Zotero 7)
uv add "pyzotero[mcp]" # + MCP server for LLM clients (Zotero 7)
Quick Start
import os
from pyzotero import Zotero
zot = Zotero(
library_id=os.environ['ZOTERO_LIBRARY_ID'],
library_type=os.environ.get('ZOTERO_LIBRARY_TYPE', 'user'),
api_key=os.environ['ZOTERO_API_KEY'],
)
# Retrieve top-level items (returns 100 by default)
items = zot.top(limit=10)
for item in items:
print(item['data']['title'], item['data']['itemType'])
# Search by keyword
results = zot.items(q='machine learning', limit=20)
# Retrieve all items (use everything() for complete results)
all_items = zot.everything(zot.items())
Core Concepts
- A
Zoteroinstance is bound to a single library (user or group). All methods operate on that library. - Item data lives in
item['data']. Access fields likeitem['data']['title'],item['data']['creators']. - Pyzotero returns 100 items by default (API default is 25). Use
zot.everything(zot.items())to get all items. - Write methods return
Trueon success or raise aZoteroError.
What ships with it
14 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.
- references/authentication.md 3.0 KB
- references/cli.md 2.4 KB
- references/collections.md 2.5 KB
- references/error-handling.md 2.7 KB
- references/exports.md 2.5 KB
- references/files-attachments.md 2.7 KB
- references/full-text.md 1.7 KB
- references/mcp.md 2.8 KB
- references/pagination.md 2.0 KB
- references/read-api.md 2.9 KB
- references/saved-searches.md 2.0 KB
- references/search-params.md 3.0 KB
- references/tags.md 2.0 KB
- references/write-api.md 3.2 KB
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.
- 9d ago First seen · 155 lines · 85 tokens per session scan A 64b8f3a60286
pyzotero is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,469 stars, last pushed yesterday), licensed MIT. It adds 85 tokens to every session and 1,716 once invoked, about $0.0004 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…
inbound-lead-enrichment
Fills in missing data for inbound leads — researches the company, identifies the person's role and seniority, finds other stakeholders at the company, checks for existing CRM relationships, and updates the lead record. Produces enriched lead data ready for qualification or outreach. Tool-agnostic.
demo-builder
Builds personalized demo assets for top prospects using the founder's product API/MCP/SDK. Researches prospect, proposes demo concepts, builds working prototype, tests it, and generates comparison report with live demo link.
create-imessage-mockup
Render pixel-accurate iMessage screenshot mockups (DM or group) from a thread JSON. Supports minimal, with-keyboard, and full iPhone 15 Pro frame variants. Outputs HTML + PNG.
industry-scanner
Daily industry intelligence scanner. Scans web, social media, news, blogs, and communities for industry-relevant events, trends, and signals. Produces a comprehensive intelligence briefing plus strategic GTM opportunity ideas. Orchestrates existing scraping skills — does not reimplement data collection.