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by Anthropicanthropics/knowledge-work-plugins26k stars
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Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.

Use this Skill: https://skilld.dev/gh/anthropics/knowledge-work-plugins/start

This session only. Nothing lands on disk.

SKILL.md

β‰ˆ70 tokens always: the name and description. β‰ˆ805 when used: this file.

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 β€” 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 β€” biomedical literature search
  • ~~literature database β€” preprint access (biology and medicine)
  • ~~journal access β€” academic publications
  • ~~data repository β€” collaborative research data (Sage Bionetworks)

Drug Discovery & Clinical:

  • ~~chemical database β€” bioactive compound database
  • ~~drug target database β€” drug target discovery platform
  • ClinicalTrials.gov β€” clinical trial registry
  • ~~clinical data platform β€” clinical trial site ranking and platform help

Visualization & AI:

  • ~~scientific illustration β€” create scientific figures and diagrams
  • ~~AI research platform β€” 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

Step 4: Optional Setup β€” Binary MCP Servers

Mention that two additional MCP servers are available as separate installations:

These require downloading binary files and are optional.

Step 5: Ask How to Help

Ask the researcher what they're working on today. Suggest starting points based on common workflows:

  1. Literature review β€” "Search ~~literature database for recent papers on [topic]"
  2. Analyze sequencing data β€” "Run QC on my single-cell data" or "Set up an RNA-seq pipeline"
  3. Drug discovery β€” "Search ~~chemical database for compounds targeting [protein]" or "Find drug targets for [disease]"
  4. Data standardization β€” "Convert my instrument data to Allotrope format"
  5. Research strategy β€” "Help me evaluate a new project idea"

Wait for the user's response and guide them to the appropriate tools and skills.

Source: SKILL.md on GitHub

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    This skill initializes a productivity dashboard by analyzing user tasks, emails, and messages to build a 'memory' system. It includes security considerations regarding the ingestion of untrusted data from external sources, which is a standard surface for indirect prompt injection. These elements are consistent with the skill's initialization and bootstrapping purpose.

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    Score: 93/100 Β· 2 sections analyzed

Signed by skilld at 3dc15bd. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last week.

Activeupdated 7 months ago

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