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 open-notebookgit 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/open-notebook)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/open-notebook"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/open-notebook/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/open-notebook"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/open-notebook.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 12 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 51 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 82 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 96 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 113 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 147 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 160 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 166 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 178 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 185 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 195 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 215 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 224 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00096 | $0.02609 |
| Opus 5.5 | $0.00038 | $0.01044 |
| Sonnet 5.5 | $0.00019 | $0.00522 |
| Haiku 4.5 | $0.00010 | $0.00261 |
Grade A, and why
open-notebook 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 25d 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 --fail --location --output docker-compose.yml \ Copies of this mod
8 near-identical copies found in the catalogue:
- open-notebook — 100% identical, 384 lines differ
- open-notebook — 88% identical, 387 lines differ
- open-notebook — 86% identical, 393 lines differ
- open-notebook — 86% identical, 393 lines differ
- open-notebook — 86% identical, 390 lines differ
- open-notebook — 86% identical, 388 lines differ
- open-notebook — 86% identical, 390 lines differ
- open-notebook — 86% identical, 388 lines differ
How it starts
The opening of the file, as written. The whole thing — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open Notebook
Overview
Open Notebook organizes sources, notes, and AI conversations into research notebooks. It supports several AI providers through Esperanto, full-text and vector search, custom transformations, and podcast generation with speaker profiles. Application storage is self-hosted; content sent to configured cloud models is not local-only.
This skill targets the latest published release observed on 2026-09-30,
v1.14.0.
Request/response contracts were checked against its official source and current main
commit 3127f14ea9dbb519f0e4ddc64a0742ca644ba6ef. Bundled helpers have mocked HTTP
regression tests; deployment, ingestion, and paid AI calls were not run against a
live instance. Deployment and remote workflow examples are illustrative.
Quick Start
Installation
Use Docker Desktop/Engine with Compose. The upstream docker-compose file configures
SurrealDB v2 and the lfnovo/open_notebook:v1-latest application image. It mounts
./notebook_data at /app/data and ./surreal_data at /mydata.
curl --fail --location --output docker-compose.yml \
https://raw.githubusercontent.com/lfnovo/open-notebook/v1.14.0/docker-compose.yml
Before starting, edit the downloaded Compose file: replace the literal
OPEN_NOTEBOOK_ENCRYPTION_KEY=change-me-to-a-secret-string value, or change it to
${OPEN_NOTEBOOK_ENCRYPTION_KEY:?Set OPEN_NOTEBOOK_ENCRYPTION_KEY} and supply that
variable. Exporting a shell variable alone does not replace the upstream literal.
Retain the key across restarts; it encrypts provider credentials, not source documents.
Set OPEN_NOTEBOOK_PASSWORD in the application's container environment when password
protection is wanted; clients then send Authorization: Bearer <instance-password>.
For a reproducible deployment, resolve and record an image digest; v1-latest moves.
docker compose up -d
docker compose logs --tail=100 open_notebook
What ships with it
8 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/api_reference.md 19 KB
- references/architecture.md 4.9 KB
- references/configuration.md 9.2 KB
- references/examples.md 8.2 KB
- scripts/_common.py 1.5 KB runs code
- scripts/chat_interaction.py 3.5 KB runs code
- scripts/notebook_management.py 2.6 KB runs code
- scripts/source_ingestion.py 6.0 KB runs code
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.
- 25d ago Changed · -107 lines · -31 tokens per session 39f3bb019462
- 26d ago Changed · +5 lines · +4 tokens per session 5391539742e1
- 1mo ago First seen · 315 lines · 123 tokens per session scan A 59fb41427cf0
open-notebook is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,777 stars, last pushed yesterday), licensed MIT. It adds 96 tokens to every session and 2,609 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
pdf-to-md
Convert PDFs and office documents to clean Markdown, with structured bundles for scientific papers. Use when extracting article structure, preparing a manuscript for analysis, or creating CSAG input.
pdf-processing-pro
Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
google-apps-script
Build Google Apps Script automation for Sheets and Workspace. Custom menus, triggers (onEdit / time-driven / form submit), dialogs, sidebars, email batches, PDF export, external API. Use whenever the user wants to automate a Google Sheet, build a Sheets menu / sidebar / dialog, hit a Sheets row from email or a…
discharge-summary-writer
Generate hospital discharge summaries from admission data, hospital course, diagnoses, procedures, and follow-up plans; use when a structured discharge document is required from clinical notes.
save-to-brain
Shared step of the marketing playbooks (research-market, plan-campaign, make-content, analyze-performance): saves a finished file to the brand and makes it searchable. It either replaces older versions or keeps dated history, then checks that the file can be found. Loaded by those playbooks; not for direct use.
fulltext-retrieval
Use when you need full-text PDFs for a list of DOIs, such as a meta-analysis screening set. Batch-downloads open-access copies via Unpaywall, PMC, OpenAlex and Crossref, lists paywalled papers for manual access, and can convert PDFs to Markdown.