Science Skills is a collection of add-ons that give AI agents structured instructions, scripts, and references for scientific research, including genomics, structural biology, cheminformatics, and literature search. Researchers use it to guide agents through specialized scientific tasks with information from databases and tools such as AlphaGenome, AFDB, and UniProt. The catalogue entries are individual skills from this collection.
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 google-deepmind/science-skills --skill workflow_skill_creatorgit clone --depth 1 https://github.com/google-deepmind/science-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/google-deepmind/science-skills/workflow_skill_creator)<a href="https://agentmods.dev/skills/google-deepmind/science-skills/workflow_skill_creator"><img src="https://agentmods.dev/badge/skills/google-deepmind/science-skills/workflow_skill_creator/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/google-deepmind/science-skills/workflow_skill_creator"><img src="https://agentmods.dev/badge/skills/google-deepmind/science-skills/workflow_skill_creator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 Agent Snooping · line 274 Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
- medium Rogue Agent · line 7 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00090 | $0.02883 |
| Opus 5.5 | $0.00036 | $0.01153 |
| Sonnet 5.5 | $0.00018 | $0.00577 |
| Haiku 4.5 | $0.00009 | $0.00288 |
Grade B, and why
workflow-skill-creator scanned grade B with 2 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
`~/.gemini/config/skills/` Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
(`urllib` preferred); Avoid libraries that require extra installation if How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow-to-Skill Distiller
Turns a completed workflow into a reusable agent skill. Specifically, this skill extracts patterns from an interaction or workflow that already happened and packages them.
[!CAUTION] You MUST complete Phase 1 (Brainstorming) before writing any code or SKILL.md content. Skipping brainstorming produces skills that are either too rigid or too vague. The brainstorming conversation is the most important part of this process.
Phase 1: Brainstorming (MANDATORY)
Have an iterative back-and-forth conversation with the user. Do NOT ask all questions at once. Pick 2-3 relevant questions per round from the bank below, refine your understanding, and ask follow-ups.
Round 1: Understand the Workflow
Start by summarizing what you observed from the workflow, then ask:
- "Here's my understanding of the workflow: [summary]. Is this accurate? What would you change?"
- "What are the expected inputs and outputs for this workflow?"
- "How often do you expect to run this workflow? Is it recurring or one-off?"
Round 2: Flexibility and Error Handling
For each step identified in the workflow, determine its rigidity:
- "For [step X], if the primary approach fails (e.g., API down, no results), should the agent: (a) ask you for guidance, (b) try alternative approaches automatically, or (c) fail loudly with an error?"
- "Are there any steps where the exact method matters (e.g., must use a specific database), vs. steps where any reasonable approach is fine?"
- "Should the skill handle edge cases silently or surface them to the user?"
Round 3: Dependencies and Resources
Before asking these questions, check which of your installed skills overlap with the workflow. If an existing skill from the science bundle covers a step, the new skill MUST reference it — do not offer a self-contained option.
- "I noticed the workflow uses functionality covered by [existing skill X, skill Y]. The new skill will reference these rather than reimplementing them. Are there any other tools or skills you'd like me to incorporate?"
- "Are there any API rate limits I should be aware of for services used in this workflow that aren't already covered by an existing skill?"
- "Are there specific files that provide important scientific context for creating this skill? For example: API documentation, reference papers, example datasets, or domain-specific notes. If so, please share them and I will incorporate their content into the skill's reference materials."
What ships with it
1 file 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 First seen · 289 lines · 90 tokens per session scan B 4833b12e3bbe
workflow-skill-creator is a skill published in the GitHub repository google-deepmind/science-skills (3,315 stars, last pushed 7d ago), licensed Apache-2.0. It adds 90 tokens to every session and 2,883 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 2 findings (reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…