Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Shoko-official/Claude-Science-System-Promptsnpx agentmods add skills/shoko-official/claude-science-system-prompts/bio-research-startWrote 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/shoko-official/claude-science-system-prompts/bio-research-start)<a href="https://agentmods.dev/skills/shoko-official/claude-science-system-prompts/bio-research-start"><img src="https://agentmods.dev/badge/skills/shoko-official/claude-science-system-prompts/bio-research-start/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/shoko-official/claude-science-system-prompts/bio-research-start"><img src="https://agentmods.dev/badge/skills/shoko-official/claude-science-system-prompts/bio-research-start.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 | $0.00049 | $0.00770 |
| Opus 5 | $0.00024 | $0.00385 |
| Sonnet 5 | $0.00010 | $0.00154 |
| Haiku 4.5 | $0.00005 | $0.00077 |
Grade A, and why
start 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 12d 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
98% identical to start — 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bio-Research Start
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
You are helping a biological researcher get oriented with the bio-research plugin. Walk through the following steps in order.
Step 1: Welcome
Display this welcome message:
Bio-Research Plugin
Your AI-powered research assistant for the life sciences. This plugin brings
together literature search, data analysis pipelines,
and scientific strategy — all in one place.
Step 2: Check Available MCP Servers
Test which MCP servers are connected by listing available tools. Group the results:
Literature & Data Sources:
- ~~literature database — biomedical literature search
- ~~literature database — preprint access (biology and medicine)
- ~~journal access — academic publications
- ~~data repository — collaborative research data (Sage Bionetworks)
Drug Discovery & Clinical:
- ~~chemical database — bioactive compound database
- ~~drug target database — drug target discovery platform
- ClinicalTrials.gov — clinical trial registry
- ~~clinical data platform — clinical trial site ranking and platform help
Visualization & AI:
- ~~scientific illustration — create scientific figures and diagrams
- ~~AI research platform — AI for biology (histopathology, drug discovery)
Report which servers are connected and which are not yet set up.
Step 3: Survey Available Skills
List the analysis skills available in this plugin:
| Skill | What It Does |
|---|---|
| Single-Cell RNA QC | Quality control for scRNA-seq data with MAD-based filtering |
| scvi-tools | Deep learning for single-cell omics (scVI, scANVI, totalVI, PeakVI, etc.) |
| Nextflow Pipelines | Run nf-core pipelines (RNA-seq, WGS/WES, ATAC-seq) |
| Instrument Data Converter | Convert lab instrument output to Allotrope ASM format |
| Scientific Problem Selection | Systematic framework for choosing research problems |
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.
- 12d ago First seen · 80 lines · 49 tokens per session scan A edfbe5bd923c
start is a skill published in the GitHub repository Shoko-official/Claude-Science-System-Prompts (10 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 49 tokens to every session and 770 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to start, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
arithmetic-evaluator
Evaluate arithmetic expressions and return numeric results. Use when a user asks an arithmetic question, requests calculation, or provides a math expression involving numbers, parentheses, and arithmetic operators.
foundations-network-science
Network-science primitives for graph systems, centrality, PageRank, communities, contagion, link prediction, and temporal networks. Use when analyzing graph structure.
research-scout
Mines academic papers, research blogs, and curator newsletters for stealable methods and frameworks. Use when scanning research for applicable techniques across AI/ML/SWE.
ai-scaling-laws
Sizes models and token budgets using Kaplan/Chinchilla scaling laws. Use when reasoning about compute-optimal N and D, tokens-per-parameter ratios, or over-training tradeoffs.
ai-ml-data-science
Builds ML, responsible-AI, and multimodal models. Use when doing data science or explaining fairness, privacy, speech, vision-language, or diffusion mechanics.
research-arxiv-scout
Discovers and triages recent arXiv papers for AI/ML, agents, and software/QA. Use when scouting categories, arXiv IDs, or source lists.