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 labarchive-integrationgit 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/labarchive-integration)<a href="https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/labarchive-integration"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/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/lord1egypt/scientific-agent-toolkit/labarchive-integration"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/labarchive-integration.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 | $0.00041 | $0.01951 |
| Opus 5 | $0.00020 | $0.00975 |
| Sonnet 5 | $0.00008 | $0.00390 |
| Haiku 4.5 | $0.00004 | $0.00195 |
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 10d 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.
This is a copy
95% identical to labarchive-integration — 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 — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LabArchives Integration
Overview
LabArchives is an electronic lab notebook platform for research documentation and data management. Access notebooks, manage entries and attachments, generate reports, and integrate with third-party tools programmatically via REST API.
When to Use This Skill
This skill should be used when:
- Working with LabArchives REST API for notebook automation
- Backing up notebooks programmatically
- Creating or managing notebook entries and attachments
- Generating site reports and analytics
- Integrating LabArchives with third-party tools (Protocols.io, Jupyter, REDCap)
- Automating data upload to electronic lab notebooks
- Managing user access and permissions programmatically
Core Capabilities
1. Authentication and Configuration
Set up API access credentials and regional endpoints for LabArchives API integration.
Prerequisites:
- Enterprise LabArchives license with API access enabled
- API access key ID and password from LabArchives administrator
- User authentication credentials (email and external applications password)
Configuration setup:
Use the scripts/setup_config.py script to create a configuration file:
python3 scripts/setup_config.py
This creates a config.yaml file with the following structure:
api_url: https://api.labarchives.com/api # or regional endpoint
access_key_id: YOUR_ACCESS_KEY_ID
access_password: YOUR_ACCESS_PASSWORD
Regional API endpoints:
- US/International:
https://api.labarchives.com/api - Australia:
https://auapi.labarchives.com/api - UK:
https://ukapi.labarchives.com/api
For detailed authentication instructions and troubleshooting, refer to references/authentication_guide.md.
2. User Information Retrieval
Obtain user ID (UID) and access information required for subsequent API operations.
Workflow:
- Call the
users/user_access_infoAPI method with login credentials - Parse the XML/JSON response to extract the user ID (UID)
- Use the UID to retrieve detailed user information via
users/user_info_via_id
What ships with it
6 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.
- 10d ago First seen · 267 lines · 41 tokens per session scan A 2f93b5aa9cd3
labarchive-integration is a skill published in the GitHub repository Lord1Egypt/scientific-agent-toolkit (3 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 1,951 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to labarchive-integration, differing in 2 lines, and is treated as a copy.
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