Open Science is a local-first, model-agnostic workbench for reproducible scientific research. Scientists use its AI agents, Python and R execution, data connectors, and traceable outputs for tasks such as literature review, analysis, simulation, and visualization across macOS, Windows, and Linux.
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 aipoch/open-science --skill customizegit clone --depth 1 https://github.com/aipoch/open-scienceWrote 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/aipoch/open-science/customize)<a href="https://agentmods.dev/skills/aipoch/open-science/customize"><img src="https://agentmods.dev/badge/skills/aipoch/open-science/customize/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/aipoch/open-science/customize"><img src="https://agentmods.dev/badge/skills/aipoch/open-science/customize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00056 | $0.02356 |
| Opus 5.5 | $0.00022 | $0.00942 |
| Sonnet 5.5 | $0.00011 | $0.00471 |
| Haiku 4.5 | $0.00006 | $0.00236 |
Grade A, and why
customize 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.
How it starts
The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customize
This Skill routes conversational customization to one of two native composers. It is not a security boundary: it helps the user draft, review, confirm, and report changes, while the application decides whether a destructive or identity-affecting operation actually takes effect.
Important: this is a framework Skill, not hard isolation. Do not claim that this Skill provides hard security isolation; it is workflow guidance only.
Route first
- For creating, revising, publishing, inspecting, or deleting a Skill, call
host.skills.read('skill-creator')and follow that internal Skill completely. Do not duplicate its authoring workflow here. - For creating or managing a Specialist, follow the Specialist workflow below.
- For a combined request, create or revise the Skill first. After publish and read-back, attach it to the selected Specialist only when the user requested that relationship.
Do not create a plan record for Specialist or Skill CRUD. Ask only about choices that materially change behavior, access, or safety. Skills and Specialists are application-managed resources, not Artifacts.
Specialist runtime
The Skill runs in the JavaScript control-plane REPL only. It uses JavaScript exclusively. Do not
use Python or R here, and do not look for host.agents or host.skills in a data kernel — they are
absent there. Specialist mutation happens through host.agents.*; Skill lifecycle work is delegated
to the internal Skill Creator above.
The Skill never uses the following, and you must not invent them:
- Do not use a Customize Specialist/Profile (there is no such profile).
- Do not use a management MCP tool, and do not route
host.agentsthroughhost.mcp(). - Do not create per-Specialist environments.
- Do not perform duplicate operations (no duplicate Specialist or duplicate operation).
- Do not automatically retry declined or stale privileged operations.
The host.agents SDK surface
The SDK is name-first and lives in the trusted calling session. JavaScript methods, inputs, and returned records all use camelCase. Methods:
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 First seen · 212 lines · 56 tokens per session scan A 729e03c353ff
customize is a skill published in the GitHub repository aipoch/open-science (4,904 stars, last pushed today), licensed Apache-2.0. It adds 56 tokens to every session and 2,356 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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