Find the best CLAUDE.md, AGENTS.md and Claude skills

Google DeepMindSkill

jaspar-database

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

Query the JASPAR database for Transcription Factor (TF) binding profiles. Use when retrieving Position Frequency Matrices (PFMs) or Position Weight Matrices (PWMs) for specific TFs, resolving gene symbols to JASPAR Matrix IDs, or getting TF metadata. Supports multiple output formats (MEME, TRANSFAC, PFM, JASPAR, YAML).

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 DeepMindAGENTS.md

mujoco_playground

google-deepmind/mujoco_playground/AGENTS.md

- Always use uv run, not bare python. Pass explicit --extra flags (e.g. --extra rl, --extra so101, --extra yam) to uv run rather than --no-sync; pyproject.toml (Python 3.12–3.13) configures PyPI as the default index, CMAKE_CXX_STANDARD=17 for reaf, and cross-platform override-dependencies (evdev on Linux only, ruckig>=0.15.3). - Always use absl (from absl import app, flags, logging) for scripts, tools, and entrypoints. NEVER use argparse. - Dependencies are managed with uv. Default make sync installs --extra rl --group dev with CUDA 13…

No other project uses it yet

Google DeepMindAGENTS.md

mujoco_warp

google-deepmind/mujoco_warp/AGENTS.md

See README.md for development setup. @CONTRIBUTING.md - PR body should be plain, concise prose. Describe the problem, what the change does, and any non-obvious tradeoffs. Bullet points listing changes are fine, but avoid section headers, structured templates, and emojis. A good PR description reads like a short paragraph to a colleague, not a form. - PR and commit messages are rendered on GitHub, so don't hard-wrap them at 88 columns. Let each sentence flow on one line.

No other project uses it yet

Google DeepMindAGENTS.md

formal-conjectures

google-deepmind/formal-conjectures/AGENTS.md

Formal Conjectures states open mathematical problems in Lean 4. It is a statement repository, not a proof repository: almost every problem is sorry. CONTRIBUTING.md is the reference for conventions, folders, and attributes. Also follow any README.md in the directory that you change. Use these detailed guides when the task needs them: Follow the style of an existing file. Start by copying one from the same directory. Search Mathlib, FormalConjecturesForMathlib/, and nearby problem files before you add a definition, API, or…

No other project uses it yet