GITHUB AGENT SKILLS / 技能收录
给你的 AI 助手
装上专业技能
我们从 GitHub 持续收录、审核并分类优质的 Agent Skills，按职业与使用场景整理，复制一行命令即可安装到 Claude Code、Cursor 等智能体。
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按 GitHub Stars 排序的优秀创作者
Microsoft
@microsoft
openclaw
@openclaw
OpenAI
@openai
The Apache Software Foundation
@apache
GitHub
@github
Anthropic
@anthropics
AutoGPT
@Significant-Gravitas
Garry Tan
@garrytan全部 Skills 196852
greenfield-parity
Use when judging whether a codebase (or a change) carries more complexity than its current spec needs — "would we build it this way from scratch?", "is this over-engineered for what it does", "this reads vibe-coded", "reconcile the existing complexity against the goal" — and when an audit that files beads must be re-runnable without duplicating findings already in the backlog. Pre-production codebases where rewrite is on the table are the primary case.
tooluniverse-phylogenetics
Production-ready phylogenetics and sequence analysis skill for alignment processing, tree analysis, and evolutionary metrics. Computes treeness, RCV, treeness/RCV, parsimony informative sites, evolutionary rate, DVMC, tree length, alignment gap statistics, GC content, and bootstrap support using PhyKIT, Biopython, and DendroPy. Performs NJ/UPGMA/parsimony tree construction, Robinson-Foulds distance, Mann-Whitney U tests, and batch analysis across gene families. Integrates with ToolUniverse for sequence retrieval (NCBI, UniProt, Ensembl) and tree annotation. Use when processing FASTA/PHYLIP/Nexus/Newick files, computing phylogenetic metrics, comparing taxa groups, or answering questions about alignments, trees, parsimony, or molecular evolution.
tooluniverse-pharmacovigilance
Analyze drug safety signals from FDA adverse event reports, label warnings, and pharmacogenomic data. Calculates disproportionality measures (PRR, ROR), identifies serious adverse events, assesses pharmacogenomic risk variants. Use when asked about drug safety, adverse events, post-market surveillance, or risk-benefit assessment.
excalidraw-diagram
Use when the user wants a workflow, architecture, protocol, concept, or Mermaid diagram converted into or out of Excalidraw, especially when the result should teach through structure, flow, and concrete evidence.
engineering-bar
Use when implementing or reviewing any non-trivial change and you need the canonical engineering quality bar — default biases, definition of done, and reviewable expectations — or when authoring a project's about/craft-and-care pillar that should reference this bar instead of restating it.
tooluniverse-pharmacogenomics
Guide pharmacogenomics (PGx) research -- drug-gene interaction lookup, CPIC guideline retrieval, variant-drug annotation, allele function status, FDA biomarker labeling, and clinical dosing recommendations. Covers the full CPIC-to-PharmGKB-to-clinical-recommendation workflow. Use when users ask about pharmacogenomics, drug-gene interactions, CPIC guidelines, genotype-guided dosing, PGx biomarkers, CYP enzyme phenotypes, or star allele interpretation.
tooluniverse-pathway-disease-genetics
Connect GWAS variants to biological pathways for drug target discovery. Maps disease-associated SNPs to causal genes via eQTL colocalization (GTEx), links genes to enriched pathways (Reactome, KEGG, MetaCyc), and identifies druggable targets within disease-relevant pathways. Use when asked to translate GWAS findings into mechanistic insights, find pathways enriched for disease genes, discover drug targets from genetic evidence, or answer questions like "What pathways are disrupted in type 2 diabetes based on GWAS data?"
documentation
Use when creating, reviewing, or auditing a codebase's documentation — README and docs/ trees, architecture/workflow diagrams, API references, formal doc sites (OpenAPI, MkDocs, Sphinx, ReadTheDocs) — and you need the bar for accessibility (concise synthesis, diagrams where structure beats prose) and accuracy over time (code-cited facts under an explicit maintenance contract).
diagnosis
Use when diagnosing a hard bug, intermittent/flaky failure, or performance regression and you need the evidence bar for the diagnosis itself — a repeatable feedback loop, ranked falsifiable hypotheses before instrumentation, tagged debug logging that gets cleaned up, and a regression test at the correct seam. Complements process skills like systematic-debugging: this is the bar for what counts as a verified root cause, not a debugging walkthrough.
tooluniverse-organic-chemistry
Teaches reasoning strategies for organic chemistry problems — reaction product prediction, spectroscopy interpretation, stereochemistry, and quantitative calculations. Use when users ask about reaction products, spectra, mechanisms, stereochemistry, or molecular formulas.
dependency-hygiene
Use when auditing or designing module boundaries and dependency chains — dependency direction, layering, cycles, public surface area, and third-party dependency admission or upgrades — in a codebase, package, or proposed change.
tooluniverse-noncoding-rna
Analyze non-coding RNAs (miRNAs, lncRNAs, circRNAs) using miRBase, LNCipedia, RNAcentral, Rfam, and target prediction databases. Covers ncRNA identification, target prediction, disease associations, expression profiling, and functional annotation. Use when asked about microRNAs, long non-coding RNAs, RNA interference, miRNA targets, lncRNA function, or ncRNA-disease associations.
cruft-cleanup
Use when reviewing or writing refactors, renames, or migrations where old interfaces may linger as aliases, re-exports, wrappers, fallback branches, deprecated flags, or other compatibility cruft. Especially relevant when changed code keeps both old and new paths alive inside the same repo.
tooluniverse-neuroscience
Neuroscience research and reasoning workflows using ToolUniverse tools. Covers computational neuroscience (rate models, integrate-and-fire neurons, synaptic plasticity, network dynamics), neuroanatomy (cortical regions, basal ganglia, cerebellum, brainstem, model organism connectomes), neurophysiology (ion channels, action potentials, synaptic transmission), neural circuits (E/I balance, oscillations, central pattern generators), synaptic dynamics (STDP, short-term plasticity, neuromodulation), neurodegenerative diseases (Alzheimer's, Parkinson's, ALS, Huntington's), and clinical neurology (cranial nerves, stroke localization, neuromuscular disorders). Use when researchers ask about brain regions, neural computation, firing rates, synaptic plasticity, connectomics, neurodegeneration, or clinical neurological questions.
code-readability
Use when judging or improving how readable and maintainable code is — naming, function shape, abstraction altitude, comment discipline, and simplicity-over-cleverness — in a diff, module, or review, especially when code works but is hard to follow.
tooluniverse-network-pharmacology
Construct and analyze compound-target-disease networks for drug repurposing, polypharmacology discovery, and systems pharmacology. Builds multi-layer networks from ChEMBL, OpenTargets, STRING, DrugBank, Reactome, FAERS, and 60+ other ToolUniverse tools. Calculates Network Pharmacology Scores (0-100), identifies repurposing candidates, predicts mechanisms, and analyzes polypharmacology. Use when users ask about drug repurposing via network analysis, multi-target drug effects, compound-target-disease networks, systems pharmacology, or polypharmacology.
ci-discipline
Use when designing, auditing, or speeding up a CI/CD pipeline, or when deciding where a check should run — gate placement by cost tier, computing each verdict once per tree, affected-only selection, merge-queue topology, queue-wait vs execution diagnosis, runtime budgets, and agent push/run habits that multiply CI runs. Complements test-rigor (what a test is worth) with where and how often checks run.
tooluniverse-multiomic-disease-characterization
Comprehensive multi-omics disease characterization integrating genomics, transcriptomics, proteomics, pathway, and therapeutic layers for systems-level understanding. Produces a detailed multi-omics report with quantitative confidence scoring (0-100), cross-layer gene concordance analysis, biomarker candidates, therapeutic opportunities, and mechanistic hypotheses. Uses 80+ ToolUniverse tools across 8 analysis layers. Use when users ask about disease mechanisms, multi-omics analysis, systems biology of disease, biomarker discovery, or therapeutic target identification from a disease perspective.