Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
Other
Builds a product wiki from the application source code or updates it after large code changes (release, refactor, many merged PRs). Records mismatches between code and claims about it (comments, docstrings, developer docs, API specs, configs). Use when the user asks to build or update the wiki/requirements/specification/docs from code.
AI/ML integration reference for Windows app development (Windows AI Foundry). Covers Windows AI APIs, LanguageModel, TextRecognizer, ImageScaler, ImageObjectExtractor, ImageObjectRemover, ImageDescriptionGenerator, SemanticSearch, ContentModeration, Phi Silica / Aion Instruct, LoRA, Windows ML, Windows ML Runtime API, ONNX Runtime, execution providers, WebGPU EP, Model Catalog, LearningModel, Foundry Local (CLI / REST API / SDK), MCP servers, App Actions, IActionProvider, Agent Launchers, DirectML, IDMLDevice, operators, tensors, and NPU.
Use when the user says 'plan a campaign', 'promote this product', 'write the copy for our sale', 'what should we push this month', or 'draft the launch for this collection'. Reads what the store actually sells, drafts the campaign around it, and stages every page and product change for approval.
Worker classification for proposed employment arrangements — analysing item by item against the three elements of 劳社部发〔2005〕12号, distinguishing employment relationships, service relationships and contracting relationships, and flagging classification gaps between the working model and the facts. Applies only to forward-looking analysis of arrangements that have not yet begun. Use when the user says "we want to use someone as a contractor," "is this a service relationship or an employment relationship," "how should this person's working relationship be classified," or describes a proposed working arrangement.
Guides actuarial work for insurance and reinsurance—pricing and rate adequacy, reserving and IBNR, loss development and triangles, mortality/morbidity and lapse assumptions, experience studies and credibility, capital and risk metrics at overview level, product design tradeoffs (life, health, P&C, annuity), and regulatory reporting concepts (NAIC, IFRS 17, Solvency II overview—not legal advice). Use when the user mentions actuary, actuarial, IBNR, loss development, reserve analysis, mortality table, pricing insurance, experience study, IFRS 17, loss ratio, combined ratio, credibility, or asks for assumption documentation and model governance for insurance products—not generic FP&A (financial-analyst), investment banking valuation (comps-analysis, dcf-model), legal policy interpretation (commercial-counsel), clinical trials, software-only implementation (senior-software-engineer), or broad GRC without actuarial models (compliance-engineer).
Guides AI risk management and governance—use-case risk assessment, model/system documentation, policies and guardrails, human oversight, third-party model/vendor review, and mapping to frameworks (NIST AI RMF, ISO 42001, EU AI Act concepts, internal AI policy). Use when classifying AI use cases, drafting AI acceptable-use policies, building risk registers, preparing model cards or DPIAs for AI, reviewing vendor LLMs, or aligning product teams with compliance—not for implementing RAG/agents (ai-engineer), running jailbreak tests (ai-redteam), or SOC 2/ISO evidence automation and technical control mapping (compliance-engineer), or general SOC 2 IT controls without AI scope (cybersecurity). For AI solution architecture in commercial or enterprise deployments, use applied-ai-architect-commercial-enterprise. For agent skills catalog standards and security review before publish, use ai-skill-manager. Safeguard infra/research: ml-infrastructure-engineer-safeguards, ml-research-engineer-safeguards.
Guidance for SPR and BLI binding characterization experiments. Use when: (1) Planning binding kinetics experiments, (2) Troubleshooting poor/no binding signal, (3) Interpreting kinetic data artifacts, (4) Choosing between SPR vs BLI platforms.
Structure prediction using Boltz-1/Boltz-2, an open biomolecular structure predictor. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources. For QC thresholds, use protein-qc. For AlphaFold2 prediction, use alphafold. For Chai prediction, use chai.
Run Boltz API workflows via the official `boltz-api` CLI — structure-and-binding, protein design/screen, small-molecule design/screen, ADME prediction, and job status/recovery. Use when the user wants to estimate, submit, monitor, fetch results for, stop, or recover a Boltz API job.
Generate templated responses for common legal inquiries and identify when situations require individualized attention. Use when responding to routine legal questions — data subject requests, vendor inquiries, NDA requests, discovery holds — or when managing response templates.
Summarize and analyze earnings calls (法說會) including financial highlights, management commentary, guidance, and analyst Q&A key takeaways. Use this skill when the user needs to digest an earnings call transcript, extract key financial data and forward guidance, compare actual results vs consensus estimates, or prepare for an investor meeting — even if they say 'summarize this earnings call', 'what did management say about next quarter', 'did they beat estimates', or 'key takeaways from the 法說會'.
Structure similarity search with Foldseek. Use this skill when: (1) Finding similar structures in PDB/AFDB databases, (2) Structural homology search, (3) Database queries by 3D structure, (4) Finding remote homologs not detected by sequence, (5) Clustering structures by similarity. For sequence similarity, use uniprot BLAST. For structure prediction, use chai or boltz.
A pre-packaged food label compliance review skill, used to review whether food labels comply with GB 7718 (General Rules for Pre-packaged Food Labels) and GB 28050 (General Rules for Nutrition Labeling of Pre-packaged Foods). Applicable scenarios: (1) the user submits food label images, text or documents and requests a compliance review; (2) the user mentions keywords such as "food label review", "label compliance", "nutrition label review", "GB 7718" or "GB 28050"; (3) the user asks to check whether a food label has missing items, errors or violation risks. Supports the 2011 and 2025 versions of the standards.
Apply Complex Adaptive Systems theory to analyze phenomena exhibiting emergence, self-organization, co-evolution, and edge-of-chaos dynamics. Use this skill when the user needs to understand why a system behaves unpredictably despite known components, model agent-based interactions that produce emergent outcomes, analyze fitness landscapes, or when they ask 'why does this system behave in ways no one designed', 'how do local interactions create global patterns', or 'why do small changes sometimes cause massive system shifts'.
Apply cutting-edge 2025 nutrition science on longevity, metabolic health, gut microbiome, and evidence-based dietary patterns for optimal vitality and disease prevention. Use when planning a diet, evaluating a nutrition claim, or applying evidence-based guidance on longevity, metabolic, and gut health.
Understand and handle essential legal matters for a solopreneur business. Use when forming a business entity, protecting intellectual property, writing contracts, understanding liability, or navigating basic legal requirements. Covers business structure selection, contracts and terms of service, IP protection basics, and when to hire a lawyer. Not legal advice — consult a lawyer for specific situations. Trigger on "legal", "business entity", "LLC", "contracts", "terms of service", "intellectual property", "liability", "legal protection".
ACTIVATE when evaluating acquisition targets, conducting M&A due diligence, planning integration strategy, analyzing synergies, preparing sale materials, assessing culture fit, valuing targets, creating merger checklists, or managing M&A transactions. Critical for executives involved in buy-side or sell-side M&A, from initial target evaluation through post-acquisition integration.
Demo manufacturing knowledge base for Taylored Systems. Shows how tribal knowledge gets captured and made queryable. USE WHEN user wants a manufacturing demo OR demonstrating to potential clients OR asks about CNC setup, machine error codes, quality inspection, startup procedures, troubleshooting, or safety OR says 'manufacturing demo', 'show me an example', 'how does it work', 'Taylored Systems demo'.
Calculate and diagnose Overall Equipment Effectiveness (OEE) by decomposing into Availability, Performance, and Quality rates. Use this skill when the user needs to measure production line efficiency, identify equipment losses, benchmark manufacturing performance, or justify capital investment — even if they say 'why is our output low', 'machine utilization report', 'production efficiency', or 'how much capacity are we losing'.
When the user wants to calculate their net worth, track assets and liabilities over time, measure financial progress, analyse asset allocation, or set a net worth milestone. Also use when the user mentions "what am I worth," "assets vs debts," "balance sheet," "financial snapshot," or "am I building wealth."
Every Hotelist feature, plus a local SQLite mirror that ranks rating-per-dollar across whole countries Trigger phrases: `find AI-rated hotels in`, `best value hotel in`, `hotels with a real gym in`, `compare hotel chains`, `rank hotels by rating per dollar`, `use hotelist`, `run hotelist`.
Guides property and casualty (P&C) insurance—commercial and personal lines, major LOBs (property, GL, workers comp, commercial auto, umbrella, specialty), underwriting and risk selection, policy triggers (occurrence vs claims-made), limits and exclusions, claims (FNOL, reserving, litigation), reinsurance and catastrophe, distribution (agents, brokers, MGAs), metrics (loss ratio, combined ratio, cat load), and state DOI/rate filing overview—not legal advice. Use for P&C insurance, property and casualty, commercial lines, workers comp, general liability, combined ratio, loss ratio, underwriting, claims-made, occurrence policy, reinsurance, catastrophe, MGA, rate filing, or FNOL—not actuarial modeling (actuary), life/health depth, legal interpretation (commercial-counsel), or GRC controls without insurance context (compliance-engineer).
Design a revenue model for a solopreneur business — how money flows in, from whom, and on what cadence. Use when deciding how to monetize a product or service, choosing between revenue streams, structuring recurring vs one-time income, or diversifying revenue. Covers all major revenue model types, selection criteria, revenue stream stacking, and the relationship between revenue model and product design. Trigger on "how will I make money", "revenue model", "monetization strategy", "revenue streams", "recurring revenue", "how to monetize", "business revenue model", "diversify income".
Evidence-based assessment of whether an SAP API/interface usage scenario aligns with the SAP API Policy (v.4.2026a). Use whenever someone asks whether a way of calling SAP is allowed or compliant—for example, Published API vs internal/private/"confidential" API status, "Documented Use", whether a third-party tool / iPaaS / middleware / RPA bot / AI agent / MCP server may call SAP APIs, agentic or generative-AI access to SAP, bulk data extraction or replication into a lake/warehouse, custom Z/Y OData or RFC/BAPI wrappers and Clean Core, ADT/developer-tooling boundaries, ODP-RFC and other "not permitted" interfaces, partner Integration Certification, or RISE integration remediation. Trigger even when the policy is not named, e.g. "are we allowed to…", "is it compliant to…", "can we connect X to SAP…", "will this break under the new API policy". Produces a sourced technical assessment with a confidence level—explicitly NOT legal advice and NOT a final SAP compliance decision.
Analyze stocks/sectors with Serenity (@aleabitoreddit)'s "supply-chain bottleneck reverse" investment logic — helping you decide how to analyze, which layer to dig into, what would confirm or falsify the thesis, and whether it is worth investing. Treat the market as a physical system rather than a list of tickers, and build the thesis before talking about instruments. Use when the user discusses investment analysis of any segment of the full AI value chain — US equities / AI supply chain / optical modules (CPO/silicon photonics/InP) / semiconductors / memory / NeoCloud / power and liquid cooling / robotics — or invokes /serenity.
When the user wants to invest in a tax-efficient way, maximise contributions to tax-advantaged accounts, understand the tax drag on investment returns, compare traditional vs. Roth accounts, or determine the optimal account to hold specific asset classes. Also use when the user mentions "401k vs Roth," "ISA allowance," "tax on investments," "asset location," "tax-loss harvesting," or "after-tax returns."
Scans a taxable brokerage account for individual lots with unrealized losses above a configurable threshold, identifies wash-sale risks by checking recent buys and forward planned buys of substantially identical securities (across all household accounts including spousal), and proposes harvest pairs (sell-for-loss + immediate buy of a similar-but-not-identical replacement). Use for year-end tax planning, monthly TLH scans, after market drawdowns, or when user mentions tax-loss harvesting, TLH, wash sale, or harvest candidates.
The Tong Jincheng perspective: viewing interpersonal relationships, social dynamics and personal growth through the thinking framework of the "deeply affectionate grandmaster" and livestream emotional-content creator. Platform compatibility: GitHub Copilot, Claude, Qwen Code, OpenCode, Cursor. Source material: transcripts of 9 first-hand videos (livestreams/dating vlogs/flirting analysis), about 200,000 characters. Core models: 5. Decision heuristics: 9. Trigger words: 「童锦程」「深情祖师爷」「用童锦程的方式」「从童锦程视角」「景辰怎么看」. Limitations: the material is mainly emotional/interpersonal content, with insufficient data on business/entrepreneurial thinking, so use with caution in purely business decision scenarios. Research date: April 2026.
Navigate Taiwan healthcare regulations including NHI system, medical device classification, drug registration, telemedicine rules, and health data protection. Use this skill when the user is building a health tech product for Taiwan, needs to understand NHI, evaluate medical device regulatory pathways, or assess telemedicine compliance — even if they say 'sell a medical device in Taiwan', 'how does NHI work', 'telemedicine regulations', or 'health data privacy in Taiwan'.
Route to the right ubi.fun skill. Use when the user mentions ubi.fun, $UBI, or trading or launching tokens on Arc. ubi.fun is a token launchpad on Arc mainnet (chain 5042, USDC gas) where tokens launched with a creator vault (all since October 4, 2026) pay their holders USDC, the platform's fees pay daily USDC to $UBI holders, and whoever routes a swap earns 5% of its fee on-chain.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.