synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and 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 synthetic-sciences/openscience --skill benchling-integrationgit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote 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/synthetic-sciences/openscience/benchling-integration)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/benchling-integration"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/benchling-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/synthetic-sciences/openscience/benchling-integration"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/benchling-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00044 | $0.02941 |
| Opus 5.5 | $0.00018 | $0.01176 |
| Sonnet 5.5 | $0.00009 | $0.00588 |
| Haiku 4.5 | $0.00004 | $0.00294 |
Grade A, and why
benchling-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 1mo 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
8 near-identical copies found in the catalogue:
- benchling-integration — 95% identical, 7 lines differ
- benchling-integration — 95% identical, 7 lines differ
- benchling-integration — 92% identical, 14 lines differ
- benchling-integration — 92% identical, 9 lines differ
- benchling-integration — 91% identical, 9 lines differ
- benchling-integration — 84% identical, 10 lines differ
- benchling-integration — 84% identical, 10 lines differ
- benchling-integration — 84% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 486 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchling Integration
Overview
Benchling is a cloud platform for life sciences R&D. Access registry entities (DNA, proteins), inventory, electronic lab notebooks, and workflows programmatically via Python SDK and REST API.
When to Use This Skill
This skill should be used when:
- Working with Benchling's Python SDK or REST API
- Managing biological sequences (DNA, RNA, proteins) and registry entities
- Automating inventory operations (samples, containers, locations, transfers)
- Creating or querying electronic lab notebook entries
- Building workflow automations or Benchling Apps
- Syncing data between Benchling and external systems
- Querying the Benchling Data Warehouse for analytics
- Setting up event-driven integrations with AWS EventBridge
Core Capabilities
1. Authentication & Setup
Python SDK Installation:
# Stable release
uv pip install benchling-sdk
# or with Poetry
poetry add benchling-sdk
Authentication Methods:
API Key Authentication (recommended for scripts):
from benchling_sdk.benchling import Benchling
from benchling_sdk.auth.api_key_auth import ApiKeyAuth
benchling = Benchling(
url="https://your-tenant.benchling.com",
auth_method=ApiKeyAuth("your_api_key")
)
OAuth Client Credentials (for apps):
from benchling_sdk.auth.client_credentials_oauth2 import ClientCredentialsOAuth2
auth_method = ClientCredentialsOAuth2(
client_id="your_client_id",
client_secret="your_client_secret"
)
benchling = Benchling(
url="https://your-tenant.benchling.com",
auth_method=auth_method
)
Key Points:
- API keys are obtained from Profile Settings in Benchling
- Store credentials securely (use environment variables or password managers)
- All API requests require HTTPS
- Authentication permissions mirror user permissions in the UI
For detailed authentication information including OIDC and security best practices, refer to references/authentication.md.
2. Registry & Entity Management
What ships with it
3 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.
- 1mo ago Changed · +6 lines d01838ac30bb
- 1mo ago First seen · 480 lines · 44 tokens per session scan A 729b2ba5d554
benchling-integration is a skill published in the GitHub repository synthetic-sciences/openscience (4,054 stars, last pushed yesterday), licensed Apache-2.0. It adds 44 tokens to every session and 2,941 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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