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 labarchive-integrationgit 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/labarchive-integration)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/labarchive-integration"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/labarchive-integration/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/labarchive-integration"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/labarchive-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Privilege Escalation · line 10 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Tool Misuse · line 175 Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
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 | $0.00052 | $0.02339 |
| Opus 5 | $0.00026 | $0.01170 |
| Sonnet 5 | $0.00010 | $0.00468 |
| Haiku 4.5 | $0.00005 | $0.00234 |
Grade A, and why
labarchive-integration 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 7d 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LabArchives Integration
Use LabArchives APIs only from current, official method pages. The public documentation is a shared notebook, not a versioned SDK reference, so verify the specific page immediately before implementing a remote operation.
Choose the Correct Surface
Do not combine these interfaces:
- Legacy ELN API: notebook trees, entries, attachments, users, searches,
exports, and site-license functions. It uses regional
*api.labarchives.comhosts,/api/<class>/<method>paths, XML for many responses, and signed query parameters. - Inventory API v1: inventory, item types, orders, storage locations, and
vendors. It documents relative
/public/v1/...paths, JSON schemas, and signedX-LabArchives-*request headers. - Product integrations: Jupyter, REDCap, Protocols.io, GraphPad Prism, SnapGene, Geneious, and others are product-specific UI or file workflows. They are not evidence of a general LabArchives OAuth 2.0 API.
Read references/api_reference.md before writing
API code and references/integrations.md before
automating an advertised integration.
Access and Credentials
LabArchives ELN developer API access is an Enterprise capability. The current Inventory FAQ limits Inventory API access to Enterprise and Enterprise Plus licensees and requires an Inventory account with API permission. Contact the institution's LabArchives team or LabArchives support for access and the development documentation supplied with it.
The environment names below are conventions of this skill, not vendor-defined standards:
LABARCHIVES_ELN_API_URL— one exact regional ELN API URL ending in/apiLABARCHIVES_ACCESS_KEY_ID— LabArchives-issued Access Key ID (akid)LABARCHIVES_ACCESS_PASSWORD— HMAC signing secretLABARCHIVES_USER_ID— optional persistent UID bound to that Access Key IDLABARCHIVES_INVENTORY_LAB_ID— required for Inventory requests
Keep secrets in the process environment or an approved secret manager. Do not
put them in YAML, source code, command-line arguments, prompts, logs, notebooks,
or committed .env files. The bundled tools never search for .env files.
What ships with it
7 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.
- 7d ago First seen · 234 lines · 52 tokens per session scan A 2dbe25bc14be
labarchive-integration 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 52 tokens to every session and 2,339 once invoked, about $0.0003 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.
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