Skills
98,873 packaged capabilities and playbooks for agents. Install any of them with one command.
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Apply when designing types, reviewing a function signature, or writing code in any statically-typed language. Make illegal states unrepresentable, brand semantic primitives, parse external data at boundaries, exhaust variants, derive from authoritative schemas.
Document any business process in a clear, structured format. Use when asked to document a process, write a process guide, create a workflow document, or map out how something works. Produces a complete process document with steps, roles, inputs, outputs, and edge cases.
Product changelog and release notes that users actually read. Covers categorization, user-facing language, visuals, and distribution. Use for: release notes, changelogs, product updates, feature announcements, versioning. Triggers: changelog, release notes, product update, version notes, what's new, feature announcement, product changelog, update log, release announcement, version release, product release, ship notes
Convert prose prompts into compact, structured XML prompt contracts through staged passes. Use when a user asks to structure, harden, formalize, debug, revise, or convert a prompt; mentions XML tags, agent drift, ambiguity, hidden assumptions, success criteria, anti-patterns, autonomous prompts, or prompt suites; or provides natural-language instructions that need to become a reliable agent contract.
Write winning proposals and quotes for a solopreneur business. Use when putting together a proposal for a potential client, structuring a sales document, pricing a project scope, or improving proposal win rates. Covers proposal structure, scoping, pricing presentation, objection pre-emption, and the psychology of persuasive proposals. Trigger on "write a proposal", "proposal template", "sales proposal", "quote for client", "how to structure a proposal", "proposal writing", "win more proposals", "client proposal".
Use when the user needs to understand, diagnose, or prevent Protheus record locks and deadlocks -- covering RecLock/MsUnlock/SoftLock/LockByName semantics, BeginTran/EndTran transaction scoping, lock leak and deadlock diagnostics (TopMemoStatus, MonitorActiveLocks, DBAccess monitor, SQL Server/PostgreSQL/Oracle lock queries), and prevention patterns (BEGIN SEQUENCE/RECOVER, lock ordering). Also triggers on Portuguese phrasing like "registro travado", "trava de registro", "deadlock", "erro de lock", "travamento no Protheus", "quem esta travando o registro", or "RecLock nao libera".
Professional Markdown to WeChat Official Account (公众号) publisher with visual style presets. Use this skill whenever the user wants to: publish an article to WeChat, create a 公众号 draft, format a blog post or technical tutorial for WeChat, apply a visual style to Markdown, or says anything like "发布到微信", "推送到公众号", "微信文章", "publish to WeChat", "WeChat draft", "公众号推文", "wechat article", "微信公众号". Also trigger when the user asks to convert Markdown to a styled HTML document for WeChat, even if they don't say "publish" explicitly. Also trigger for translation/repost requests: "全文翻译", "转载", "translate and publish", "repost", or when the source article is in English and the user wants to publish it to WeChat. Also trigger for "视频号", "短视频", "竖屏视频", "生成视频", "video", "short video", or "WeChat Channels". This skill handles credentials, image uploads, 13 style presets (3 core + 7 extend + unlimited custom), automatic cover generation, full-article translation, and draft creation end-to-end.
Python SDK for inference.sh - run AI apps, build agents, and integrate with all models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python
Adversarial Quarto-vs-Beamer parity QA. A critic agent compares the Quarto HTML render to the Beamer PDF benchmark for content/visual parity; a fixer agent applies fixes; loops until APPROVED or two consecutive rounds turn up nothing new (fallback cap 5 rounds). Use when user says "qa the quarto", "check parity", "does the html match the pdf?", "quarto matches beamer?", or after a translate-to-quarto run. Requires both the `.qmd` rendered and a `.pdf` benchmark.
Skill dedicated to a wall construction pitfalls guide. Covers emulsion paint and putty, wallpaper and wall panels, microcement and artistic paint, substrate treatment and leveling, cracking, hollowing and mold, wall storage and utilization, and overall wall topics across the full process, integrating the highlights of the Xi'an Renovation Classroom member knowledge base in reverse order to help users avoid pitfalls in wall construction with less hassle.
Publish quantitative analysis or existing JPG/PNG, HTML, PDF as a Quant Buddy shareable live page or real-time dashboard, supporting creation, update, reuse, acceptance and public link delivery. Applies to pages such as single-stock profiles, valuation and financials, index moves, multi-factor screening, commodity daily reports, templates, sharing shells and cards. Also use when the user provides a QuantBuddy live page URL and asks for interpretation. When /quant-buddy-view, /qbv, qbv or QBV is explicitly invoked and the request is not purely consultation, code maintenance or documentation explanation, treat it by default as a shareable live page task. Inputs that uniquely identify an A-share name, short name or code, or a simple request for single-stock comprehensive analysis (such as "贵州茅台", "600519", "分析一下贵州茅台") all default to a single-stock quick page; first verify via QBS and reply with the complete single-stock analysis, then new_asset_page in the same round, without the user needing to add "generate a page". When a WebAgent host requires financial questions to deliver both Q&A and a live page uniformly, one-off quotes, price changes, valuation, concept explanations and colloquial status questions are also handed off to this skill after the first QBS answer. Without such a host agreement, one-off questions are answered by QBS; operations such as review, monitoring, charting, backtesting and K-line still default to live page intent. Do not create a page when the user explicitly does not want a web page or wants text only.
When the user wants to do a quarterly review, reflect on the past quarter, plan the next quarter, reset strategic priorities, or says things like 'quarterly review,' 'end of quarter,' 'Q1/Q2/Q3/Q4 review,' 'quarterly planning,' 'what should we focus on next quarter,' 'strategic reset.' The 90-minute big sibling of weekly-review.
LLM workloads on open-source Ray (pinned to 2.57) — OpenAI-compatible serving with ray.serve.llm (vLLM-backed LLMConfig + build_openai_app) and batch inference with ray.data.llm (build_processor). Corrects the stale defaults a model produces — the archived ray-llm repo and its YAML configs, hand-rolled vLLM engines inside plain Serve deployments, the removed build_llm_processor name, deprecated boolean stage flags, top-level LLMServer/LLMRouter imports, free-form accelerator strings, one-deployment-per-LoRA-adapter designs — with the 2.57 idioms (stage configs, placement_group_config over hand-rolled PGs, deployment_config autoscaling, dynamic LoRA multiplexing, prefix-cache-affinity routing, the full OpenAI endpoint surface). Use when writing, reviewing, or productionizing LLM serving or batch inference on Ray. Classic-ML Ray (Train/Tune/Data/Serve/clusters) lives in the sibling ray skill.
Use this skill whenever creating outreach — a cold email, a LinkedIn message, a follow-up, or a multi-step sequence — for a company, a contact, a list, or a signal. Use it even when the user doesn't say "outreach": any request to write to, contact, message, or get in front of a prospect or account goes through here. Covers picking the hook, matching the org's voice, choosing the sequence shape, and staging everything for approval. Trigger phrasings: "reach out to", "draft outreach", "email this company", "message this prospect", "follow up with", "build a sequence", "contact these visitors". Also use it for strategic outreach questions ("how should our cold emails sound", "what cadence should we run") — the output is then a point of view grounded in the org's saved voice, not a sequence.
Write and edit human-facing project technical text for scanning, wherever it lives — README, specs, design notes, plans, reports, runbooks, changelogs, and project memory, not only docs/ or StrictDoc. Use whenever creating or revising these records, without waiting for an explicit style request; also for 说人话、去 AI 味、精简文档、短语分点、PPT 式表达. Prefer Chinese phrases, lists, and compact comparison tables while preserving facts, conditions, evidence, and required structure. Not a detector-evasion or creative-writing skill.
Scrape and search Reddit posts using Apify. Use when you need to find Reddit discussions, track competitor mentions, monitor product feedback, discover pain points, or analyze subreddit content. Supports keyword filtering, time-based searches, and subreddit-specific queries.
Design and audit referral, invite, affiliate, ambassador, creator, team-invite, waitlist, viral loop, reward, attribution, fraud-control, promotion, and lifecycle referral systems for SaaS, mobile apps, games, marketplaces, developer tools, and communities. Use when creating or improving referral programs that should grow users or revenue without spam, fake scarcity, abuse, or trust damage.
Performance best practices for Relay applications. Use when optimizing data fetching, reducing re-renders, configuring caching, or improving time to first meaningful paint. Covers query placement, @defer, pagination, fetch policies, garbage collection, fragment granularity, and server-side filtering. Companion to the relay-best-practices skill which covers correctness and architecture.
Detects and prevents manual edits to release-please managed files (CHANGELOG.md, version fields in package.json, pyproject.toml, Cargo.toml). Provides conventional commit templates. Use when editing changelogs, version bumps, release files, or when user mentions "release", "changelog", "version bump", or "conventional commits".
Build production-grade frontend UI that does not look AI-made or borrowed: identity from the client's world, references, tokens, interaction, a11y/SEO, slop audit. Use when building any page, component or dashboard; when the owner says the result looks generic; or when a product needs a visual language of its own.
Interactively prepare a code repository for publication — LICENSE, NOTICE, AUTHORSHIP, README sections, package metadata, .gitignore, community docs (CONTRIBUTING/CODE_OF_CONDUCT/SECURITY/CHANGELOG), .github templates (issues/PR/CI/dependabot), a promo "more from the author" block, and conditional EU/Germany legal compliance (CRA, AI Act, GDPR, Impressum, product liability). Includes a dedicated authorship wizard that documents human decisions, judgment, direction, and art direction with jurisdiction-aware legal framing. Use when setting up a new repo for release, adding missing legal/meta/community files, writing an AUTHORSHIP record for AI-assisted work, or asking "prepare this repo for GitHub / open-sourcing".
Render a finished BS report as a self-contained HTML page — score hero, filterable claims, readable on a phone, prints to a clean PDF. Use when the user wants to open, share, print, or show a report to someone who is not going to read a markdown table, or asks for "the HTML version", "something I can send", "a shareable page", or "make this readable".
Turn a brief or existing feature into testable requirements: behavior, acceptance criteria, quality constraints, and data and permission rules. Use when notes or a concept need FR/NFR requirements or acceptance criteria before design or build, or when checking which requirements a shipped feature meets.
Brainstorm and stress-test research ideas as a senior scholar colleague would. Runs a multi-turn dialogue that clarifies the seed question (or generates one from cold start), probes it conversationally, launches a parallel deep literature scan across published and working-paper sources, critiques the question adversarially, generates 2–3 alternative framings, assesses feasibility (delegating to the find-data skill when available), and writes a research brief to the working directory. Trigger when the user asks to brainstorm a research idea, stress-test a research question, workshop a project, develop a new paper idea, assess novelty of a question, evaluate whether an idea is worth pursuing, refine a research direction, or check whether an idea clears a top-journal bar. Also trigger on phrases like "brainstorm with me", "is this novel", "has anyone done this", "what should I work on", "help me think through this idea", "workshop this question", "stress-test this", "poke holes in this", "new research idea", "research project idea", or when the user describes a half-formed question and asks for feedback. Use regardless of field but tuned for empirical economics and adjacent social sciences.
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.