Claude skills and agent skills

Google DeepMindSkill

literature-search-arxiv

google-deepmind/science-skills/skills/literature_search_arxiv/SKILL.md

Search for scientific papers, preprints, and publications on arXiv. Extract metadata, abstracts, and download full-text PDFs or HTML versions of papers. Use when the user asks to find research papers, literature, or specific arXiv IDs.

Google DeepMindSkill

literature-search-biorxiv

google-deepmind/science-skills/skills/literature_search_biorxiv/SKILL.md

Browse and filter life sciences, biology, and medical preprints from bioRxiv and medRxiv. Supports fetching paper metadata by DOI, and browsing by date range with category and keyword filters. Keyword filtering is local, so date ranges MUST be narrow (1-4 weeks) with a category to prevent timeouts.

Google DeepMindSkill

literature-search-europepmc

google-deepmind/science-skills/skills/literature_search_europepmc/SKILL.md

Search Europe PMC for scientific literature and download open-access full texts and PDFs. Retrieve full-text XML/plain text by PMCID, get citation lists and bibliography.

Google DeepMindSkill

opentargets-database

google-deepmind/science-skills/skills/opentargets_database/SKILL.md

Query Open Targets Platform for target-disease associations, drug target discovery, tractability/safety data, genetics/omics evidence, known drugs, for therapeutic target identification.

Google DeepMindSkill

pdb-database

google-deepmind/science-skills/skills/pdb_database/SKILL.md

Use when you want to search for or download experimentally-determined 3D structures for biomolecules (proteins, nucleic acids, bound ligands). Supports searching by sequence similarity, structure similarity, chemical and other attributes. Also use to get metadata about biomolecular structure experiments.

Google DeepMindSkill

predictingthepast

google-deepmind/science-skills/skills/predictingthepast/SKILL.md

Ancient text restoration, attribution, dating, contextualization, and embedding via Aeneas (Latin) / Ithaca (Ancient Greek). Use when asked to "restore", "attribute", "date", "contextualize", "find parallels", "where was it written", "when was it written", "embed", or "analyze" an ancient text, inscription, or epigraphic document, or when the user mentions "Aeneas", or "Ithaca".

Google DeepMindSkill

pubchem-database

google-deepmind/science-skills/skills/pubchem_database/SKILL.md

Query PubChem, search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics. Use when a user asks about a specific chemical, drug, or molecule.

Google DeepMindSkill

pymol

google-deepmind/science-skills/skills/pymol/SKILL.md

Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis.

Google DeepMindSkill

quickgo-database

google-deepmind/science-skills/skills/quickgo_database/SKILL.md

Query the QuickGO and Evidence & Conclusion Ontology (ECO) REST API. Use this when you need to map genes to biological processes, molecular functions, or cellular components, find genes associated with a specific pathway/GO term, or explore the Gene Ontology hierarchy. Do not use for querying drug targets (use OpenTargets) or mechanistic signaling pathway diagrams (use KEGG).

Google DeepMindSkill

reactome-database

google-deepmind/science-skills/skills/reactome_database/SKILL.md

Query the Reactome database (Analysis and Content Services). Use when the user asks about pathway analysis, gene list enrichment, retrieving results by token, finding unmapped or not-found identifiers, mapping identifiers, reaction participants (inputs, outputs), pathway hierarchy (including top-level pathways), diagram export, cross-reference mapping, or searching the knowledgebase.

Google DeepMindSkill

string-database

google-deepmind/science-skills/skills/string_database/SKILL.md

Query the STRING database for protein-protein interactions (PPIs), functional enrichment, and homology. Use when the user asks about interactions between specific proteins, interaction evidence, confidence scores, protein interaction partners, or pathway enrichments.

Often used withena-database·usfiscaldata·simpy

Google DeepMindSkill

ucsc-conservation-and-tfbs

google-deepmind/science-skills/skills/ucsc_conservation_and_tfbs/SKILL.md

Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser. Use when analyzing whether genomic variants or regions are evolutionarily conserved, functionally important, or bounded by TF regulators across major projects (ENCODE, JASPAR, ReMap).

Google DeepMindSkill

unibind-database

google-deepmind/science-skills/skills/unibind_database/SKILL.md

Queries the UniBind database for experimentally validated transcription factor (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets, downloading binding site coordinates (BED/FASTA) for local analysis, or listing available datasets by species, cell line, or TF name. Don't use to query specific intervals, locations, genes, motif models or expression data.

Google DeepMindSkill

uniprot-database

google-deepmind/science-skills/skills/uniprot_database/SKILL.md

Access protein metadata, function, taxonomy, and sequences across UniProtKB, UniParc, and UniRef. Use when searching for proteins, mapping identifiers, or retrieving functional annotations and publications. Don't use for sequence alignment, protein folding, or sequence similarity search (use specialized skills for those tasks).

Often used withusfiscaldata·ena-database·gwas-database

Google DeepMindPipes a download into a shellSkill

uv

google-deepmind/science-skills/skills/uv/SKILL.md

Checks whether the uv Python package manager is installed and installs it if missing. Ensures uv is on PATH. Use when another skill requires uv as a prerequisite.

Google DeepMindSkill

workflow-skill-creator

google-deepmind/science-skills/skills/workflow_skill_creator/SKILL.md

Distills a completed user workflow or interaction into a reusable agent skill. Use when the user asks to turn their workflow, interaction, or multi-step process into a skill, or when they say "make this a skill", "create a skill from what we just did", "package this workflow" or similar. Do not use for creating skills from scratch without an existing workflow (use a generic skill-creator for that).

Google DeepMindSkill

xmanager_cloud

google-deepmind/xmanager/.agents/skills/xmanager/SKILL.md

Launches, manages, and troubleshoots XManager Cloud (XMC) experiments. A MUST READ before launching any XMC experiment, orchestrating jobs on Kubernetes/GKE, or configuring experiment flags. Don't use for internal corporate launches.

Google DeepMindSkill

agentic-ecology-bioacoustics

google-deepmind/agentic_ecology/skills/agentic-ecology-bioacoustics/SKILL.md

Provides bioacoustic analysis capabilities for ecologists and researchers using the perch-hoplite Python package. A typical use case is to use agile modeling to bootstrap the creation and deployment of a bespoke detector for targeted species on an existing collection of passive acoustic monitoring recordings. Use when processing and annotating audio recordings for bioacoustic applications.

Google DeepMindSkill

agentic-ecology-camera-traps

google-deepmind/agentic_ecology/skills/agentic-ecology-camera-traps/SKILL.md

Provides capabilities to run SpeciesNet detector and classifier on camera trap images, extract crop-level feature embeddings, and populate a Hoplite vector database for downstream search and agile modeling. Use when ingesting camera trap images, classifying wildlife photos, or indexing camera trap data.

Google DeepMindSkill

agentic-ecology-init

google-deepmind/agentic_ecology/skills/agentic-ecology-init/SKILL.md

Initializes a local uv-managed project directory for agentic ecology workloads. Sets up Python dependencies using reference pyproject.toml and uv.lock, configures workspace rules, and ensures Agentic Ecology skills are discoverable. Use when initializing a new project workspace or bootstrapping a clean environment.