Skills de Claude Code · página 43

Analyze metabolomics data end-to-end — metabolite identification, quantification (TIC normalization, batch correction), differential analysis, and pathway interpretation. Use for processing mass-spec metabolomics output, normalization choice, untargeted metabolomics workflows, and integrating with other omics layers.

Metabolomics pathway analysis — metabolite identification (HMDB, KEGG, ChEBI), pathway mapping (Reactome, KEGG, MetaCyc), disease associations, enzyme/gene linkage. Use for metabolite-to-pathway-to-disease connections, BridgeDb-based ID conversion, and integrating metabolomics with gene-level pathway analyses.

Metabolomics research — metabolite identification, study analysis, and database searches across HMDB, MetaboLights, Metabolomics Workbench, KEGG. Use for annotating mass-spec features to known metabolites, finding metabolomics studies of a disease, and structured metabolomics research reports with metabolite-pathway mapping.

Microbiome and metagenomics analysis using MGnify, GTDB taxonomy, ENA sequencing data, and EuropePMC literature. Covers taxonomic classification, genome quality assessment, biome-clinical phenotype linkage, and pathway interpretation. Use for amplicon/shotgun metagenomics study analysis.

Microbiome research using MGnify, GTDB, ENA, OLS (ENVO biomes), and EuropePMC. Covers study discovery, taxonomic profiling, host-microbe interaction analysis, and biome-by-condition queries. Use for microbiome study selection, organism-environment associations, and clinical-microbiome literature review. Distinct from analytical workflow (use tooluniverse-metagenomics-analysis for that).

Cross-species genetic analysis using model organism databases (MGI mouse, ZFIN zebrafish, FlyBase fruit fly, WormBase worm, SGD yeast, RGD rat, GBIF taxonomy). Maps human genes to orthologs, retrieves phenotype/expression/functional data, assesses gene function conservation, and identifies the best animal model for studying a human gene or disease.

Molecular cloning assembly design — Gibson Assembly (overlap design for seamless multi-fragment joining) and Golden Gate Assembly (Type IIS / BsaI / BbsI design with unique 4-bp fusion overhangs). Use when you need to plan how to join DNA fragments into a construct, design assembly overlaps/overhangs, or decide between cloning methods. Covers the domestication (internal-site removal), overhang-uniqueness, and overlap-Tm rules. For PCR primers to generate the fragments, see tooluniverse-primer-design.

Multi-omics integration — orchestrate per-layer analysis (transcriptomics, proteomics, epigenomics, genomics, metabolomics) then perform cross-omics correlation, multi-omics clustering, and pathway-level integration. Use for integrative systems-biology analysis, multi-modal disease characterization, and cross-omics biomarker discovery.

Comprehensive disease characterization across genomics, transcriptomics, proteomics, and pathways for systems-level understanding. Identifies therapeutic opportunities and biomarker candidates by integrating multi-layer molecular data. Use for full-omics disease deep-dive reports, mechanism mapping, and biomarker-and-target identification from multi-omics data.

Compound-target-disease network construction and analysis for drug repurposing, polypharmacology discovery, and multi-target drug design. Uses STRING, BioGRID, ChEMBL, DGIdb, OMIM, OpenTargets. Use for off-target effect prediction, network-based drug repurposing, and identifying molecules with desired multi-target profile.

Neuroscience research workflows: neuroanatomy, neural circuits, neurotransmitter biology, neurological/psychiatric disease genetics, neural-protein function. Uses Allen Brain Atlas, WormBase (C. elegans connectome), UniProt for neural proteins, PubMed for primary literature. Use for brain-region biology, neural development, neurodegeneration mechanisms (Alzheimer's, Parkinson's, ALS), and synaptic-protein characterization.

Non-coding RNA analysis — miRNAs (miRBase, miRDB targets), lncRNAs (LNCipedia, RNAcentral), circRNAs, snoRNAs, and other ncRNA classes. Distinct mechanisms per class — miRNAs repress mRNA; lncRNAs scaffold/decoy/enhance. Use for ncRNA function prediction, miRNA-target prediction, lncRNA functional annotation, and ncRNA-disease association queries.

Organic chemistry reasoning guide for reaction product prediction, mechanism analysis (electrophilic/nucleophilic substitution, addition, elimination, pericyclic, radical), and spectroscopy interpretation (1H/13C NMR, IR, MS). Reasons from first principles (electron flow, kinetic vs thermodynamic) rather than pattern-matching named reactions. Use for organic synthesis problems and mechanism explanations.

Compute and interpret validated bedside clinical risk scores and pretest probabilities for an INDIVIDUAL patient — pick the right score for the scenario, gather inputs, run the deterministic calculator tool, and read the result against an interpretation table. Covers CHA2DS2-VASc (AF stroke risk), HAS-BLED (bleeding on anticoagulation), CURB-65 (pneumonia severity / admit decision), qSOFA (sepsis screen), Child-Pugh + MELD-Na (cirrhosis severity / transplant priority), Wells DVT and Wells PE (VTE pretest probability), ASCVD (10-year cardiovascular risk / statin decision), and eGFR CKD-EPI (kidney function / drug dosing). Use when asked things like "stroke risk for this AF patient", "should this patient be anticoagulated", "pneumonia severity — admit or not?", "sepsis screen this patient", "DVT/PE pretest probability", "10-year cardiovascular risk", "cirrhosis severity / MELD score", or "eGFR / kidney function". Pairs CHA2DS2-VASc with HAS-BLED to weigh anticoagulation. NOT for polygenic/genetic risk (use tooluniverse-polygenic-risk-score), NOT for population-level epidemiology/incidence (use tooluniverse-epidemiological-analysis), and NOT for diagnostic test sensitivity/specificity/likelihood-ratio math (use tooluniverse-diagnostic-test-evaluation).

FASTQ quality control and adapter/quality-trimming decisions with local NGS tools — run FastQC on raw reads, summarize a project with MultiQC, interpret per-base sequence quality, per-base N content, adapter content, overrepresented sequences, sequence duplication and GC content, and decide whether (and how) to trim with fastp / Cutadapt before downstream analysis. seqkit for read counts/stats/subsampling. Use when someone asks "run QC on my FASTQs", "are my reads good quality?", "do I need to trim adapters?", "interpret this FastQC report", "what does this WARN/FAIL mean", "why are overrepresented sequences flagged", "should I quality-trim before alignment", "make a MultiQC summary", or "clean up these reads with fastp". NOT for differential expression / DEG analysis (use tooluniverse-rnaseq-deseq2), NOT for read alignment, coverage, or variant calling (use tooluniverse-variant-analysis / tooluniverse-sequence-analysis). Honest: shells out to real local binaries; if a tool is missing it emits an install plan and stops rather than inventing QC numbers, and it never auto-trims or overwrites raw FASTQs.

Genome-ASSEMBLY discovery, QC, and replicon mapping for any organism (bacteria, archaea, fungi, and beyond) using NCBI Datasets. Resolves an organism name or taxid to assemblies, picks the reference/representative or best-quality assembly, pulls assembly QC metrics (total length, contig/scaffold N50, contig count, GC%, assembly level, RefSeq category), enumerates chromosomes and plasmids via per-replicon sequence reports, and compares candidate assemblies on quality. Use for "what genomes are available for [organism]", "assembly stats / N50 / GC content for [GCF_/GCA_ accession]", "how many plasmids does [strain] have", "compare assemblies for [species]", "find the reference genome for [taxon]", "is this assembly Complete Genome or just contigs". NOT for gene-level orthology/synteny (use tooluniverse-comparative-genomics), plant gene structure (use tooluniverse-plant-genomics), de novo assembly from raw reads (no tool exists), or taxonomy-only name/lineage lookups.

Dereplicate a putative natural product and assign its chemical taxonomy. Use to answer "is [compound] a known natural product", "what microbe/organism produces [compound]", "what chemical class is [compound]", "dereplicate this metabolite (by formula/exact mass/InChIKey/SMILES)", or "classify this molecule into ChemOnt". Searches NPAtlas for known microbial natural products (producing organism + literature reference), assigns the ChemOnt kingdom→superclass→class→subclass hierarchy via ClassyFire, resolves systematic IUPAC names to structure via OPSIN, and cross-references identity in PubChem. NOT for general drug/compound identity or ADMET (use tooluniverse-chemical-compound-retrieval / tooluniverse-small-molecule-discovery) and NOT for metabolomics pathway/enrichment analysis (use tooluniverse-metabolomics skills).

Generate high-converting App Store screenshots by analyzing your app's codebase, discovering core benefits, and creating ASO-optimized screenshot images using Nano Banana Pro.

对当前文本、对话或显式文件内容做结构化分析，并区分事实、判断与待确认项。

内容工厂专用写作 Skill，生成批量文案、短视频脚本和图片提示词，并输出可回写的 contentFactoryWorkspacePatch。

将品牌定位、价值观、受众画像、语气风格、内容样例、危机回应和表达禁区，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的品牌人设知识库。适用于用户要求“整理品牌人设”“沉淀品牌口吻”“把品牌资料变成可复用语气库”“维护品牌 persona pack”的场景。

将品牌产品资料、规格参数、卖点证据、FAQ、价格权益、竞品区别和合规边界，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的产品资料知识库。适用于用户要求“整理产品知识库”“沉淀产品 FAQ”“把品牌产品资料变成项目资料”“维护产品资料包”的场景。

将文章整理为可转播客音频的源文本（下游负责真实音频合成）。

将活动目标、用户路径、渠道分工、物料资产、时间节奏、风险预案和复盘结论等资料，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的运营类知识库。适用于用户要求“整理活动 / Campaign 运营知识库”“沉淀运营 SOP”“把运营资料变成项目资料”“维护运营知识库”的场景。

将选题日历、栏目矩阵、素材资产、发布节奏、复盘结论和内容边界等资料，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的运营类知识库。适用于用户要求“整理内容运营知识库”“沉淀运营 SOP”“把运营资料变成项目资料”“维护运营知识库”的场景。

内容工厂专用复核 Skill，检查事实依据、平台适配、AI 味、风险和人工确认建议。

生成可直接发布的内容主稿（默认公众号长文风格）并自动生成 1 张头图，最终以 write_file 落盘。

为文章或视频生成平台封面图，并写回主稿（封面场景优先使用本技能）。

根据目标说明生成一份可直接在聊天区渲染的 A2UI 表单，复用 Lime 现有表单协议。

将增长目标、指标体系、渠道策略、实验计划、复盘结论、资源约束和停止条件，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的增长策略知识库。适用于用户要求“整理增长知识库”“沉淀增长策略”“把增长计划变成项目资料”“维护增长实验资料包”的场景。

仅在用户显式使用 @配图/@修图/@重绘/@image，或已明确确认调用画图功能后，根据文本描述生成配图素材（非封面场景）。

兼容旧版 Agent Knowledge 编译流程的 deprecated 兜底 Builder。仅用于未知或历史 pack 类型；标准 persona / data pack 必须优先委托内置专用 Builder Skill。

【外部资产库】读取项目参考资料（/project）或风格参考（/styles）。

将直播排期、货盘节奏、场控流程、主播话术、互动机制、异常预案和复盘指标等资料，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的运营类知识库。适用于用户要求“整理直播运营知识库”“沉淀运营 SOP”“把运营资料变成项目资料”“维护运营知识库”的场景。

检索图片、背景音乐、音效、视频等素材；图片优先直搜候选，其他资源走任务主链。

将团队 SOP、交付流程、角色职责、项目复盘、FAQ、决策边界和升级机制，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的组织经验知识库。适用于用户要求“整理组织知识库”“沉淀团队 SOP”“把交付经验变成项目资料”“维护组织 know-how”的场景。

读取本地或工作区 PDF 内容，并输出结构化解读结果。

将访谈稿、聊天记录、简历、公开内容、业务资料、案例和既有 DOCX/Markdown 文档，提炼成可被 AI 长期调用的个人 IP 知识库。适用于用户要求“生成个人知识库”“整理成个人 IP 成品知识库”“为创始人/专家/讲师/主播/顾问建立AI知识库”“把资料变成个人IP底层提示词/写作风格库/故事素材库/话术库”的场景。

根据目标说明生成一份可直接讲述、继续导出的单文件演示稿 Markdown，并落到工作区供右侧 viewer 预览。

将用户分层、社群 SOP、触达节奏、转化话术、活动机制和服务边界等资料，整理成符合 Agent Knowledge v0.6 document-first 标准、可被 AI 安全调用的运营类知识库。适用于用户要求“整理私域 / 社群运营知识库”“沉淀运营 SOP”“把运营资料变成项目资料”“维护运营知识库”的场景。

联网检索并产出结构化研究报告，强调结论、证据、风险与建议。

联网信息检索与趋势调研（优先产出可引用结论，而非原始片段堆砌）。

通过站点适配器检索指定站点内容（GitHub、知乎、B站、36Kr、linux.do、什么值得买、Yahoo Finance、X 长文）。

提炼当前文本、对话或显式文件内容中的关键要点与结论。

提交音频或视频转写任务，生成逐字稿或字幕任务。

将当前文本、对话或显式文件内容翻译成目标语言，并保留原意与关键信息。

优化文稿排版与可读性，不改变原始事实与核心表达。

解析外部 URL 内容，并沉淀为可阅读的文本结果。

提交视频生成任务，并触发前端视频生成流程。

根据目标说明生成可直接预览的单文件 HTML 网页，并落到工作区供右侧 viewer 预览。

Lime CLI 平台技能，统一任务创建、状态查询、重试、队列与幂等语义。

通过 Lime CLI 创建播客文本整理任务。

通过 Lime CLI 创建素材检索任务。

通过 Lime CLI 创建文稿排版优化任务。

通过 Lime CLI 创建链接解析任务。

Before answering a substantive question, quietly check whether the user has already resolved this question in the past.

List the Claude Code plugins currently enabled for the agent, read straight from settings.json.

Weekly self-audit playback. Surface patterns from the user's past week that they probably cannot see themselves.

Find commitments the user made in the last two weeks and did not follow through on. A promises audit.

Discover recurring behaviors from memory and offer to formalize them as scheduled jobs.

List the agent's current skills, memory files, plugins, subagents, hooks, and a settings summary plus dashboard URLs. The user-facing discovery path for everything the operator can edit.

Show how the user's thinking on a specific topic has evolved over time. A chronological narrative with turning-point callouts.

Create a git commit with a summary of changes

Generate a creative greeting for the user

Configure CC Safety Net rulebooks for user, project, or shareable GitHub scope.

Analyzes codebases to understand structure, tech stack, patterns, and conventions. Use when onboarding to a new project, exploring unfamiliar code, or when asked "how does this work?" or "what's the architecture?

Convex backend development guidelines. Use when writing Convex functions, schemas, queries, mutations, actions, or any backend code in a Convex project. Triggers on tasks involving Convex database operations, real-time subscriptions, file storage, or serverless functions.

Designs database schemas, indexing strategies, query optimization, and migration patterns for SQL and NoSQL databases. Use when designing tables, optimizing queries, fixing N+1 problems, planning migrations, or when asked about database performance, normalization, ORMs, or data modeling.

Designs REST and GraphQL APIs including endpoints, error handling, versioning, and documentation. Use when creating new APIs, designing endpoints, reviewing API contracts, or when asked about REST, GraphQL, or API patterns.

Designs software architecture and selects appropriate patterns for projects. Use when designing systems, choosing architecture patterns, structuring projects, making technical decisions, or when asked about microservices, monoliths, or architectural approaches.

Designs and implements testing strategies for any codebase. Use when adding tests, improving coverage, setting up testing infrastructure, debugging test failures, or when asked about unit tests, integration tests, or E2E testing.

Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.

Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alerting, or resilience patterns.

Manages Git workflows including branching, commits, and pull requests. Use when working with Git, creating commits, opening PRs, managing branches, resolving conflicts, or when asked about version control best practices.

Analyzes and optimizes application performance across frontend, backend, and database layers. Use when diagnosing slowness, improving load times, optimizing queries, reducing bundle size, or when asked about performance issues.

Patterns for parallel subagent execution using Task tool with run_in_background. Use when coordinating multiple independent tasks, spawning dynamic subagents, or implementing features that can be parallelized.

Implements authentication, authorization, encryption, secrets management, and security hardening patterns. Use when designing auth flows, managing secrets, configuring CORS, implementing rate limiting, or when asked about JWT, OAuth, password hashing, API keys, RBAC, or security best practices.

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", "check my site against best practices", or "web interface guidelines".

Integrated 3-statement financial model: linked income statement, balance sheet, and cash flow

Create and manage scheduled and price-triggered automations.

Event tracker: earnings dates, economic releases, conferences, regulatory events

Investment deck QC: number consistency, data-narrative alignment, IB language, formatting audit

Financial model audit: structural checks, formula validation, integrity testing

Competitive landscape analysis: positioning, scorecards, moat assessment, market share trends

Comparable company analysis: operating metrics, valuation multiples, peer benchmarking

DCF valuation: free cash flow projections, WACC, terminal value, sensitivity analysis

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

Post-earnings analysis report: beat/miss breakdown, estimate revisions, thesis impact, charts

Pre-earnings analysis: consensus estimates, key metrics to watch, bull/base/bear scenarios

Stock screening and idea generation: quantitative screens, thematic analysis, shortlist

Full equity research initiation: company research, financial model, valuation, charts, 30-50 page report

Inline HTML widgets: charts, dashboards, data tables rendered directly in the chat via ShowWidget

Interactive web dashboards: stock trackers, sector heatmaps, portfolio monitors — served via preview URL

Update financial model with new quarterly actuals, revised estimates, and updated price target

Daily research briefing: overnight news, pre-market movers, earnings, macro events

First-time user onboarding to set up investment profile, watchlists, portfolio, and preferences.

Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions \"deck,\" \"slides,\" \"presentation,\" or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.