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

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

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 DeepMindAGENTS.md

simply

google-deepmind/simply/AGENTS.md

Simply is a minimal JAX-based research codebase for LLM training and inference. It emphasizes minimal abstractions for rapid iteration on frontier research. The codebase supports Gemma, Qwen, and DeepSeek model families with multi-host distributed training.

Google DeepMindCLAUDE.md

simply

google-deepmind/simply/CLAUDE.md

Simply is a minimal JAX-based research codebase for LLM training and inference. It emphasizes minimal abstractions for rapid iteration on frontier research. The codebase supports Gemma, Qwen, and DeepSeek model families with multi-host distributed training.

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 DeepMindAGENTS.md

agentic_ecology / assets

google-deepmind/agentic_ecology/skills/agentic-ecology-init/assets/AGENTS.md

- Environment Management: This repository is managed exclusively with uv. All dependency resolution and environment setup are handled by uv. The soundfile library is guaranteed to be available in this environment; do not waste steps verifying its installation. - Agent Artifacts: You MUST store artifacts (Python scripts, Markdown documents, etc.) in the agent_workspace directory inside the repository's root directory so that the user can inspect your work. Do NOT create or commit any temporary, throwaway, or scratch files anywhere else.…

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.

Google DeepMindSkill

agentic-ecology-ui

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

Guidelines and templates for creating a generic web UI to visualize, rank, filter, and annotate vector databases. The UI has a hierarchical structure covering database selection, label selection/definition, ranking/filtering configuration, and row visualization/annotation. Use when building, serving, or adapting an interactive web UI for Hoplite vector databases.

Google DeepMindAGENTS.md

padic-ml

google-deepmind/padic-ml/AGENTS.md

Precision Convention: - We should not hardcode precision. Use jnp.int_ or jnp.float_. User scripts should control precision via globally setting jax_enable_x64 themselves.