LobsterBio - Use

v1.1.406

Runs bioinformatics analysis with Lobster AI -- single-cell RNA-seq, bulk RNA-seq, genomics (VCF/GWAS), proteomics (mass spec/affinity), metabolomics (LC-MS/...

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Install

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Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for cewinharhar/lobsterbio-use.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "LobsterBio - Use" (cewinharhar/lobsterbio-use) from ClawHub.
Skill page: https://clawhub.ai/cewinharhar/lobsterbio-use
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install cewinharhar/lobsterbio-use

ClawHub CLI

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npx clawhub@latest install lobsterbio-use
Security Scan
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Purpose & Capability
The name/description (bioinformatics via Lobster AI) align with the SKILL.md instructions: it expects the lobster CLI, Python, LLM provider keys, and access to public bio databases. However the registry-level manifest at the top of the package incorrectly lists no required binaries/env vars/primary credential while the embedded SKILL.md explicitly requires 'lobster', 'python3', and one of several LLM provider credentials. This mismatch between registry metadata and the included SKILL.md is an inconsistency worth clarifying.
Instruction Scope
The SKILL.md stays within the stated purpose: it instructs the agent to run the lobster CLI, use workspace directories, call `lobster query` and `lobster command`, and access public bio resources. There are no instructions to read unrelated system files or exfiltrate data to unexpected endpoints. It does, however, instruct non-interactive initialization that will persist provider credentials into workspace or global config files (described behavior).
Install Mechanism
This is an instruction-only skill with no install spec. The SKILL.md recommends installing 'lobster-ai' from PyPI (traceable source) which is appropriate for the described functionality. No arbitrary download/extract URLs or hidden installers are present in the package.
!
Credentials
The SKILL.md legitimately requires one LLM provider key (Anthropic/OpenAI/Google/OpenRouter/AWS Bedrock/Azure or local Ollama). That is proportionate to a tool that delegates work to LLMs. The concern is that the agent is instructed to run non-interactive `lobster init` which will write credentials into `.lobster_workspace/.env` (workspace-scoped) or optionally `~/.config/lobster/credentials.env` if `--global` is used. Writing secrets to disk is expected for a CLI but is sensitive — users should confirm the workspace path and file permissions before use. Also the package-level metadata does not advertise these required env vars, creating a packaging/visibility gap.
Persistence & Privilege
The skill does not request always:true and is user-invocable; it will create and use workspace files (.lobster_workspace/, provider_config.json, .env) by design. The optional `--global` flag would write to system user config (~/.config/lobster/) — the SKILL.md notes this is not the default and warns to avoid it unless needed. This is expected behavior for a CLI but increases blast radius if an automated agent is permitted to run init with global flags.
What to consider before installing
This skill appears to be a legitimate usage guide for the Lobster AI CLI, but there are two things to check before installing or running it: 1) Metadata mismatch: The package registry metadata at the top claims no required binaries or env vars, but the embedded SKILL.md requires the 'lobster' CLI, python3, and an LLM provider credential. Ask the publisher/maintainer to correct the declared requirements so mounting or policy tooling can enforce them. 2) Credential handling: The recommended non-interactive initialization will write your chosen provider credentials into the workspace `.lobster_workspace/.env` (mode 0600) or, only if `--global` is used, into `~/.config/lobster/credentials.env`. Before running `lobster init --non-interactive`, decide which provider you trust, do NOT pass multiple provider keys, and avoid the `--global` flag unless you understand the implications. Inspect `.lobster_workspace/.env` after initialization and remove or rotate keys if you are unsure. Practical steps: verify the upstream project (GitHub/PyPI links), install in an isolated environment (virtualenv/container), run `lobster config-test --json` manually to confirm connectivity, avoid agent-run global init, and review workspace files and permissions. If you need the skill to run autonomously, require additional review: confirm the agent will only use workspace-scoped config and will never run with `--global` or write credentials to system-wide locations.

Like a lobster shell, security has layers — review code before you run it.

latestvk978wvb5agqfj0a984n1c3sfzx82egg2
355downloads
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4versions
Updated 1mo ago
v1.1.406
MIT-0

Lobster AI Usage Guide

Lobster AI is a multi-agent bioinformatics platform. Users describe analyses in natural language -- Lobster routes to 22 specialist agents across 10 packages automatically.

Requirements

  • Binaries: lobster CLI (pip install lobster-ai), Python 3.12+
  • Credential: Exactly ONE LLM provider key as env var (not all — pick one):
    • ANTHROPIC_API_KEY | GOOGLE_API_KEY | OPENAI_API_KEY | OPENROUTER_API_KEY
    • AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY (Bedrock — both required)
    • AZURE_AI_ENDPOINT + AZURE_AI_CREDENTIAL (Azure — both required)
    • Ollama: no key needed (local models)
  • Optional: NCBI_API_KEY for faster PubMed/GEO
  • Writes: .lobster_workspace/ (data, credentials in .env mode 0600, outputs)
  • Global config (--global flag, NOT default): ~/.config/lobster/ — avoid unless needed
  • Network: LLM provider API + public bio databases (GEO, SRA, PRIDE, MetaboLights)

Docs Discovery

The docs site at docs.omics-os.com exposes LLM-friendly raw markdown:

RouteUse
/llms.txtIndex of all pages (title + URL + description)
/llms-full.txtFull content dump of all free pages
/raw/docs/{slug}.mdRaw markdown for a specific page

Workflow: Fetch /llms.txt first to discover slugs, then fetch individual pages via /raw/docs/{slug}.md.

Example: https://docs.omics-os.com/raw/docs/tutorials/single-cell-rnaseq.md

Two Modes

This skill supports coding agents in two modes:

Orchestrator -- The agent calls lobster query --json --session-id programmatically, parses structured output, and chains multi-step analyses. See agent-patterns.md.

Guide -- The agent teaches a human user what to type in lobster chat or lobster query. See the routing table below for which docs page to fetch.

Quick Start

# Install (PyPI -- preferred)
pip install 'lobster-ai[full]'
# or: uv tool install 'lobster-ai[full]'

# Configure (uses env var -- never pass raw keys on command line)
lobster init --non-interactive --anthropic-key "$ANTHROPIC_API_KEY" --profile production

# Run analysis (always pass -w and --session-id together)
lobster query -w ./my_analysis --session-id "proj" --json "Download GSE109564 and run QC"

# Inspect workspace (no tokens burned, ~300ms)
lobster command data --json -w ./my_analysis

Source: github.com/the-omics-os/lobster | PyPI: pypi.org/project/lobster-ai

Routing Table

You want to...Docs slugSkill reference
Install & configuregetting-started/installation--
Configuration optionsgetting-started/configuration--
Use the CLIguides/cli-commandscli-reference.md
Orchestrate programmatically--agent-patterns.md
Analyze scRNA-seqtutorials/single-cell-rnaseq--
Analyze bulk RNA-seqtutorials/bulk-rnaseq--
Analyze proteomicstutorials/proteomics--
Understand data formatsguides/data-formats--
Search literature / datasetsagents/research--
Analyze genomicsagents/genomics--
Analyze metabolomicscase-studies/metabolomics--
ML / feature selectionagents/ml--
Drug discoveryagents/drug-discovery--
Visualize resultsagents/visualization--
Troubleshootsupport/troubleshooting--
See case studiescase-studies/{domain}--
All agent capabilitiesagents--
Extend Lobster (dev)--Use lobster-dev skill

To fetch a docs page: https://docs.omics-os.com/raw/docs/{slug}.md

Hard Rules

  1. Always use --session-id for multi-step analyses -- loaded data persists across queries
  2. Use lobster command --json for workspace inspection (no tokens burned, ~300ms)
  3. Research Agent is the ONLY agent with internet access -- all others operate on loaded data
  4. Never skip QC before analysis -- always assess quality first
  5. Use --json flag when parsing output programmatically
  6. Check data is loaded before running analysis steps (lobster command data --json)
  7. Default workspace: .lobster_workspace/ -- override with -w <path>
  8. Fetch docs on demand from docs.omics-os.com/raw/docs/{slug}.md -- don't guess workflows

Agent Overview

22 agents across 10 packages. Supervisor routes automatically based on natural language.

AgentPackageHandles
Supervisorlobster-aiRoutes queries, coordinates agents
Research Agentlobster-researchPubMed, GEO, SRA, PRIDE, MetaboLights search (online)
Data Expertlobster-researchFile loading, downloads, format conversion (offline)
Transcriptomics Expertlobster-transcriptomicsscRNA-seq + bulk RNA-seq: QC, clustering, trajectory
Annotation Expertlobster-transcriptomicsCell type annotation, gene set enrichment (child)
DE Analysis Expertlobster-transcriptomicsDifferential expression, pseudobulk, GSEA (child)
Proteomics Expertlobster-proteomicsMS + affinity import, QC, normalization, batch correction
Proteomics DE Expertlobster-proteomicsProtein DE, pathway enrichment, KSEA, STRING PPI (child)
Biomarker Discoverylobster-proteomicsPanel selection, nested CV, hub proteins (child)
Metabolomics Expertlobster-metabolomicsLC-MS/GC-MS/NMR: QC, normalization, PCA/PLS-DA, annotation
Genomics Expertlobster-genomicsVCF/PLINK: QC, GWAS, variant annotation
Variant Analysis Expertlobster-genomicsVEP annotation, ClinVar, clinical prioritization (child)
ML Expertlobster-mlML prep, scVI embeddings, data export
Feature Selection Expertlobster-mlStability selection, LASSO, variance filtering (child)
Survival Analysis Expertlobster-mlCox models, Kaplan-Meier, risk stratification (child)
Drug Discovery Expertlobster-drug-discoveryDrug target validation, compound profiling
Cheminformatics Expertlobster-drug-discoveryMolecular descriptors, fingerprints, similarity (child)
Clinical Dev Expertlobster-drug-discoveryTrial design, endpoint analysis, safety signals (child)
Pharmacogenomics Expertlobster-drug-discoveryPGx variants, drug-gene interactions (child)
Visualization Expertlobster-visualizationUMAP, heatmaps, volcano plots, dot plots (Plotly)
Metadata Assistantlobster-metadataID mapping, metadata standardization (internal)
Protein Structure Vizlobster-structural-vizPDB fetch, PyMOL visualization, RMSD

Per-agent docs: https://docs.omics-os.com/raw/docs/agents/{domain}.md

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