Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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Internal step of plan-feature: from an already-designed SPEC (product half `designed`), fill the **engineering half** and generate the planning artifact set scaled to the feature's size (XS/S → SPEC-only with ≥ 2 phases in the SPEC, last = Hardening & PR; M/L → full set with a hardening phase), freeze one compact ACCEPTANCE.md for every size, and register the roadmap entry. Docs only — never code.
Use before creating, changing, or writing code against Salesforce metadata, to find out what already exists in the org with the right tool. Routes each question to metadata grounding, scoped SOQL with sf data query, sf sobject list or describe, sf org list metadata, source retrieval, or local files, and covers orgs and setups where grounding is not available. Use to check whether an object, field, picklist, permission set, page, app, or flow already exists before creating one, confirm field names, types, and picklist values before writing Apex, LWC, SOQL, or Flow logic, list every field on an object or every member of a metadata type, find automation that runs on an object, or explain how something in the org is configured and who can access it. DO NOT TRIGGER for whole-org overviews, org comparison, or drift (use dx-org-analyze), metadata file structure or XML shape (platform-metadata-api-context-get), or Data Cloud DLO and DMO schema (data360-code-extension-generate).
Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.
Conducts blameless postmortems that transform failures into learning opportunities by documenting timelines, quantifying impact, performing root cause analysis (5 Whys, fishbone diagrams), and defining corrective actions with owners and deadlines. Use when analyzing failures, outages, incidents, or negative outcomes, conducting blameless postmortems, identifying corrective actions, learning from near-misses, establishing prevention strategies, or when user mentions postmortem, incident review, failure analysis, RCA, lessons learned, or after-action review.
Every KDP Niche Finder bucket as a local research database — rank niches across buckets Trigger phrases: `find a kdp niche`, `rank kdp niches`, `which book niche is rising`, `kdp niche research`, `best low-content book niche`, `use kdpnichefinder`, `run kdpnichefinder`.
Install and use Perplexity's pplx CLI for live web search and query-relevant page snippets from the terminal. Use to search the web, look up current information or news, get query-relevant excerpts from specific URLs, or install and authenticate the pplx command.
STEP 1 of the PPTX-from-layouts pipeline. Profile a PowerPoint template to discover its real slide-master layouts and emit a layout catalog + render config. Use when the user wants to "use my own PowerPoint template", "see what layouts my deck has", "onboard a template", "profile this pptx", or before authoring slides against a custom (non-Inner-Chapter) template. Pairs with pptx-author (Step 2) and pptx-from-layouts (Step 3).
Constraint transparency: analyzes an artifact structurally, then analyzes what its own analysis concealed. Produces a conservation law AND a constraint report showing what was maximized, what was sacrificed, and what to investigate next. The only AI skill that knows what it can't see.
Compare intended product outcomes against observed results to close the launch-to-learning loop: collect post-launch evidence, distinguish expected from observed from uncertain from inferred claims, update assumptions, assess feature health, and choose among continue/improve/harvest/pivot/pause/retire — including retirement lifecycles with deprecation, migration, customer treatment, and retained reusable learning. Do not use for incident postmortems or root-cause analysis (routes to incident-learning or site-reliability-engineering); do not use for analytics instrumentation or metric dashboard design (routes to product-analytics-and-measurement); do not use arbitrary thresholds as universal retirement rules — decisions require human judgment and context.
Authoritative reference for Anthropic products. Use when users ask about product capabilities, access, installation, pricing, limits, or features. Provides source-backed answers to prevent hallucinations about Claude.ai, Claude Code, and Claude API.
Universal meta-skill that bootstraps ANY software project regardless of programming language. Auto-generates 15-30+ hyper-detailed, project-specific coding skills BEFORE writing code. Language-agnostic: works with TypeScript, Python, Go, Rust, Java, C#, Swift, Kotlin, PHP, Ruby, and polyglot projects. AGGRESSIVE version enforcement: EVERY technology version MUST be verified via real-time lookup — never use memorized versions. Generates skills for architecture, security, performance, privacy, testing, error handling, accessibility, observability, data modeling, API design, DevOps. Each skill enforces zero-bug standards with concrete code examples, anti-patterns, and measurable budgets. Triggers on: "bootstrap", "new project", "start project", "create project", "set up", "generate skills" — use BEFORE any code exists.
Use when you have already determined the scope of Discover (P0/P1/P2) and now need to quickly establish the Level-0 north star (memory) and the Level-1 map-layer index skeleton (components/products) of `.aisdlc/project/`, so that evidence can later be filled in module by module without double-writing or drift.
Use when you are about to start Discover on an existing project but are still unclear about which entry points can serve as evidence (run/test/ci/contract/ops) and which modules to tackle first (P0/P1/P2), and you worry that the scope will spiral out of control and become unmaintainable.
Best practices for building performant, testable PySpark ETL pipelines with Spark SQL and Apache Iceberg. Use when writing or reviewing PySpark jobs, designing joins and window functions, working with map/array higher-order functions, or building idempotent cumulative/snapshot table merges.
Predicts defect-prone code using change frequency, complexity metrics, and historical bug patterns. Use when predicting defects before they escape, analyzing root causes of test failures, learning from past defect patterns, or implementing proactive quality management.
React Router v7 framework mode conventions for route modules, data loaders, actions, and progressive enhancement. Use when building file-based routes with loaders/actions, handling form submissions with Form/useFetcher/useSubmit, adding route ErrorBoundary components, revalidating data after mutations, or migrating Remix-style route modules to React Router v7.
Use this skill whenever the user wants to search, verify, screen, compare, or organize real academic papers and return traceable paper addresses or links, especially for literature reviews, core-paper lists, recent papers, high-quality paper screening, CNKI traceability, DOI/publisher pages, Google Scholar discovery, top conference/journal screening, or when the user explicitly asks for “真实文献”, “文献地址”, “可追溯链接”, “核心文献”, “筛选优秀文献”, “国外优秀文献”, or “顶会顶刊”. If the topic is broad or underspecified, use this skill to narrow the scope first before searching.
The reflection agent. Use it right after another skill produces an artifact such as a rewrite from polish-prose, a rebuttal, an abstract, a preflight fix, or a tailored draft to critique that output against the stated goal, the paper's .paper-memory/profile.yml, the relevant rubric, and past .paper-memory/lessons.md, then decide whether it actually improved. Trigger words include reflect, self-critique, did this get better, did my edit help, regression check, review my own output, iterate, refine, second pass, sanity-check the rewrite, and "is the new version actually better". Runs a bounded self-refine / Reflexion loop, guards against regressions, and appends durable, deduplicated, dated lessons to .paper-memory/lessons.md via a stdlib script so the toolkit gets sharper each paper. Reflection adds cost; it only pays off when there is a measurable target.
Human-feel writing — when polishing, refining, or rewriting someone else's text, preserve the presence of the person behind the words. Use when: the user brings a piece of their own writing and asks to polish, refine, revise, tighten, or rewrite it, with asks like "help me fix this up" or "how is this passage". Also applies to rework scenarios where, after ghostwriting, the user says "this feels too AI-generated", "there's no human feel", or "I can't feel me in it". Trigger words: polish copy, refine, help me revise, rewrite, revise this passage, human feel, AI feel. Two built-in layers: underlying principles (when to touch and how to touch) + a post-check list (does what was touched have an AI feel, based on Wikipedia Signs of AI writing / blader humanizer).
Critical analysis of research papers evaluating methodology, claims-evidence alignment, and contribution significance. Triggers on: "critique this paper", "review this research", "analyze this study", "evaluate the methodology", "is this paper sound". NOT for formatting or submission readiness, use manuscript-review.
Review code against the canonical architecture quality Rule set, including boundaries, dependency direction, cohesion, cycles, contract stability, coupling, composition, change surface, unreachable code and deprecation discipline. Cognitive-only atomic skill; output is a findings list.
Reviews Red Hat Developer Hub pull request code on GitHub in rhdh, rhdh-operator, rhdh-plugins, or community-plugins. Use for a GitHub PR URL or number, "review this PR", analysis-only review, or posting inline comments. For label and merge-readiness triage of the overlay PR backlog, use /rhdh-overlay.
Salla OAuth 2.0 and merchant token management — the Salla delta on standard OAuth: Easy Mode (tokens via the app.store.authorize webhook, no callback — published apps) vs Custom Mode (authorization-code, dev/testing only), the offline_access scope, single-use refresh tokens needing a per-merchant refresh lock, and the User Info endpoint. Use before writing any Salla token-handling code. Lifecycle events → salla-app-lifecycle; webhook verification → salla-webhooks; API usage → salla-api-core.
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.
A complete guide to using Semi Design components, including MCP tool workflows, common patterns, validation after page generation, and best practices. Use this skill when you need to look up Semi Design components, generate component pages, or resolve usage issues.
Send an email to a mailing list via the SchemaVaults mail-server `/api/send` route, using either the `sendEmailToMailingList()` helper or the `schemavaults-send-email send-to-mailing-list` CLI from `@schemavaults/send-email`. Use when any server-side TypeScript/JavaScript code needs to send a notification to a mailing list audience — **or when Claude Code itself wants to send a one-shot notification at the end of a task** (preferred — invoke the CLI via `bunx schemavaults-send-email send-to-mailing-list …`; fallback — write a short script to `/tmp/` and run it with `bun`).
Ahrefs API analyst (extension). Reads referring domains, backlinks, organic keywords, and content explorer data via the tested @ahrefs/[email protected] server. Pairs with seo-backlinks for multi-source confidence weighting.
Technical SEO audit across 9 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow protocol. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".
Build, configure, and test Agentforce agents on Salesforce. Covers agent setup, topics, actions (Flow, Apex, PromptTemplate, External Service), Agent Scripts for deterministic FSM-based agents, PromptTemplate authoring, GenAI Models API, metadata structure, and agent testing via the Testing Center and CLI. Activate on Agentforce agents, .agent files, .agent-meta.xml, .agentTopic-meta.xml, .agentAction-meta.xml, GenAiFunction, GenAiPlugin, PromptTemplate, Agent Script, or agent testing workflows.
Write and review technical text with project-aware ASD-STE100 Issue 9 guidance. Use for technical documentation, code comments, procedures, software text, safety instructions, and controlled-language reviews. Do not use for creative writing, casual conversation, or general translation.
Pre-flight checks, reliability acceptance testing, and format review tooling for Skill creation. Use this skill when a user creates, substantially reworks, or reviews a Skill and needs to identify unstable instruction following, output drift, validation-modality mismatches, or missed constraints in older Skills, or to check Harness contracts, candidate binding evidence, fault injection, directory structure, business flows, and security risks. Do not use for: replacing domain validators, code review, application functional testing, or general programming tasks.
Applies the user's engineering standards during substantial technical work: preserve scope, use current evidence, delegate independent parts, and complete authorized outcomes. Use during substantial implementation, debugging, refactoring, or multi-part delivery work.
Design, audit, and evolve physical source and package structures that expose real architectural boundaries while keeping related behavior together. Use when creating or reviewing repository trees, deciding where files or packages belong, reducing flat folders, organizing by feature, route, screen, use case, bounded context, workflow or endpoint, structuring frontend state/data/UI ownership and design systems, making hexagonal inside/outside boundaries visible, locating ports, adapters and composition roots, structuring BFF routes, planning folder migrations, or enforcing package and import direction. For one module's logical responsibility, deepening, splitting, or caller contract use codebase-design; for repository-wide architecture investment discovery use improve-codebase-architecture. A physical flattening alone is not a reduce-system-complexity result.
Build a reusable visual style guide from reference images - how the style renders what the references show and what they never show - as markdown files other skills read. Use when the user has reference images or screenshots and wants new images or video to match their look
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.