Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
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HTTP clients for frontend and Node.js. Covers Axios, Fetch API, ky, and ofetch. Includes interceptors, error handling, retry logic, and auth token management. Use for configuring API clients and HTTP communication. USE WHEN: user mentions "HTTP client", "Fetch API", "ky", "ofetch", "HTTP wrapper", "retry logic", "token refresh", asks about "which HTTP client to use", "HTTP request library", "API client setup", "request interceptors" DO NOT USE FOR: Axios-specific questions - use `axios` instead; GraphQL - use `graphql-codegen` instead; tRPC - use `trpc` instead; WebSocket connections
Apply Socratic questioning — systematic inquiry via clarification, assumption-probing, evidence-testing, perspective-shifting, implication-tracing, and meta-questions — to coach learning or surface hidden assumptions in a person's reasoning. Use this skill when the user is explicitly facilitating learning, coaching a person through their own thinking, or needs a structured questioning sequence to probe a held belief, even if they say 'play devil's advocate on this claim' or 'how should I coach my team through this problem via questions'. Do NOT use for open-ended brainstorming, information gathering, or requirements-discovery question lists where no belief is being probed.
Remove signs of AI-generated writing from academic medical papers. Use when editing or reviewing manuscripts to make them sound more natural and professionally written. Based on Wikipedia's "Signs of AI writing" guide, adapted for medical literature. Detects and fixes patterns including: inflated significance claims, superficial -ing analyses, vague attributions, AI vocabulary words, copula avoidance, excessive hedging, generic conclusions, informal word choices (linked/beyond/via/where/yield), overly assertive causal claims, and artificially condensed expressions. Preserves legitimate academic transitions (Notably, Prior studies have shown, etc.).
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
IntelliJ IDEA MCP for Java code analysis, testing, refactoring, and project navigation. Use when: (1) Checking Java compilation errors (get_file_problems is more accurate than LSP for multi-module Maven), (2) Performing rename refactoring across the codebase, (3) Searching code or finding files in the project. Requires IDEA to be running with MCP plugin connected.
Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
Azure OpenAI image generation CLI tool (gpt-image-1.5 / gpt-5.1). Generates images from text, edits images with AI, and describes image contents. Use when the user wants to (1) generate images using Azure OpenAI, (2) edit existing images with AI, (3) explain image contents. Triggers on "画像を生成", "画像を編集", "画像の説明", "generate an image", "edit this image", "describe this image", "imgenで".
Comprehensive frontend design skill — 23 commands for shaping, auditing, polishing, and refining UI. Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, empty states. Handles UX review, visual hierarchy, info architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems/tokens. Also use for bland designs needing boldness, loud designs needing quiet, live browser iteration, or ambitious visual effects. Not for backend-only or non-UI tasks.
Build a whole feature by breaking a plan into tasks and running implement-and-review on each. Given a plan or feature, decompose it into tracer-bullet vertical-slice tasks (via the to-tasks skill — acceptance contracts + gate flags + dependencies), then execute the task DAG (independent tasks in parallel) by running implement-and-review for each per-task FE/BE cross-reviewed TDD build, integrate tasks in dependency order with per-task acceptance, and finish with a feature-wide full-review, leaving tests/build green. Opus orchestrates breakdown, scheduling, integration, and final review; per-task building is implement-and-review's job. Use to ship/build a multi-task feature end-to-end. For a single scoped task call implement-and-review directly. Distinct from models-consensus (deliberation only, produces no code) and from ship — ship is the idea→PR conductor, including the interactive spec/plan phases and PR delivery, while implement-feature is the plan→built-feature DAG executor with no spec phase and no PR.
Collaboratively improve an article or bullet points section-by-section. Use when user says "improve this article", "make this better", "edit my draft", or "help me revise this piece". Surfaces non-obvious insights, applies a target style, and pauses for user input at every step.
Find deepening opportunities in a codebase, referencing the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly coupled modules, or make a codebase more testable and AI-navigable.
Transforms a rough, unpolished prompt idea into a precise, structured AI coding prompt. Automatically researches the current project context (stack, file structure, conventions, git history) before generating. This skill should be used when the user provides a vague or "dirty" prompt idea and asks to refine, improve, or rewrite it — e.g. "improve this prompt", "refine my prompt", or simply describes what they want done in rough terms. NOT when the user wants the work done or planned rather than the prompt itself — deep-plan produces the plan; just doing the task needs no prompt skill.
Score and route an inbound lead (form fill, demo request, content download) on ICP fit (0-40), intent (0-30), and urgency (0-30) -> priority tier + response SLA, then draft a first-touch email and route to the right AE. Use when: "qualify this inbound lead", "score and route [name] from [company]", "is this demo request worth calling", "route this form fill", "triage inbound", "inbound lead", "demo request scoring". Pulls the contact from HubSpot and gates through qualify_lead. Not for the AE handoff document itself — that is ae-handoff-brief-skill.
Guides information security engineering—implementing and operating security controls, identity and access systems, encryption and secrets management, security tool integrations (SIEM, EDR, SOAR), cloud guardrails, hardening baselines, and remediation engineering for vulnerabilities. Use when building SSO/RBAC/PAM patterns, configuring KMS or certificate lifecycle, deploying WAF/DLP or EDR connectors, writing security-as-code policies (OPA, SCPs, CIS benchmarks), integrating logging to SIEM, automating security workflows, or validating control fixes—not for SOC triage (soc-analyst), pentesting (penetration-tester, network-pentester, web-pentester), red team (red-team-specialist), CI gates only (devsecops), platform provisioning without security ownership (infrastructure-engineer), CISO/exec program (chief-information-security-officer), security program strategy (cybersecurity), GRC program and audit prep (compliance-specialist), or product tenancy isolation (product-infrastructure-security-engineer).
Write an infrastructure-as-code review checklist and conduct a structured review of Terraform, CloudFormation, Pulumi, or Ansible code. Use when asked to review IaC code, audit infrastructure configurations, check cloud security posture, or produce a reusable IaC review checklist. Produces a structured review report with severity-categorized findings, remediation guidance, and a reusable checklist.
Initialize the Playwright trio (@playwright/test + @playwright/cli + playwright-mcp) in a pnpm monorepo, including an e2e/visual testing skeleton, MCP configuration, AI skills generation, and AI memory updates. Includes a built-in postmortem and troubleshooting guide for headless browser CPU overload incidents: it can diagnose high CPU usage (100%) in headless mode, browser hangs, leftover Chromium processes that cannot exit, and 3D WebGL rendering performance issues on large displays; it provides emergency stop-loss steps and a long-term regression checklist. Triggered when the user mentions Playwright initialization, large-display visual testing, e2e test setup, Playwright monorepo configuration, pw_core/pw_visual MCP, and so on. Also applies to troubleshooting scenarios such as headless browser performance issues, headless CPU 100% diagnosis, cleanup of leftover Chromium processes, handling browser processes that cannot exit, and performance tuning for large-display 3D rendering.
Create and use Inngest middleware for cross-cutting concerns. Covers the middleware lifecycle, creating custom middleware, dependency injection with dependencyInjectionMiddleware, encryption via @inngest/middleware-encryption, Sentry error tracking via @inngest/middleware-sentry, and custom middleware patterns.
Monitor buyer intent signals for a target-account list — job postings, funding, headcount growth, leadership changes, first-party engagement — pulled live from Apollo organization data and the Epiphan CRM, scored into an account heat ranking, and gated through qualify_lead so only net-new accounts are marked hot. Use when: "track intent signals for [accounts]", "which accounts are showing buying signals", "who is in-market right now", "hot accounts this week", "intent digest", "is [company] hiring AV staff", "funding or hiring signals in [vertical]". Not for job-change people lists (linkedin-sales-navigator-alt-skill) or lookalike expansion (lookalike-customer-finder-skill).
Reference: shared framework for managing internal investigations from intake through final memo — privileged investigation log, document processing with needle-finding, source coverage tracking, Q&A against the log, memo drafting, and audience summaries. Loaded by /investigation-open, /investigation-add, /investigation-query, /investigation-memo, and /investigation-summary; not invoked directly.
Reference: implementation-planning framework for international hiring — EOR vs. entity decision framing, cross-functional triggers for tax/finance/HR, structured outside-counsel briefing requests, and a persistent gap tracker. Loaded by /expansion-kickoff and /expansion-update; not invoked directly.
Conduct iterative interviews to clarify scope, surface constraints, and reach a "do / don't do / done" agreement before starting non-trivial work. Use when receiving an ambiguous request, a vague task description, or before entering plan mode for any non-trivial implementation. Skip for one-line concrete fixes ("rename foo to bar"), single-fact questions, or when scope, constraints, and acceptance criteria are already specified. Supports requirements definition, debugging investigation, architecture review, security review, documentation creation, and general exploration.
Open a new internal investigation matter — run the intake registration, generate an evidence-source list, and create a running investigation log. Use when a complaint or allegation comes in and a lawyer needs to set up a confidential investigation workspace.
Query an in-progress investigation log — what witnesses said, where statements contradict each other, what evidence gaps exist, and what the most probative evidence is on each issue. Use when a lawyer needs to query the investigation record without re-reading every entry.
Draft audience-specific summaries from an investigation memo — an HR version, a management version, or an outside-counsel version. Use when the investigation memo needs to reach audiences that should not see the full confidential work product.
Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.
Grade IRAC essays — structure, issue spotting, rule accuracy, depth of analysis, and organization. Never writes the essay or shows a model answer; tracks patterns across exercises. Use when the user says "grade my IRAC", "check my essay", or "I wrote this, give me feedback".
Craft irresistible offers using direct response marketing principles. Use when designing pricing offers, creating product bundles, building value stacks, or need risk reversal strategies. Includes 7-part offer formula, psychological triggers, and guarantee frameworks.
Answer a quick Feishu/DingTalk question with a "is this a problem?" reply — pattern-matching against your calibration. Use when the user says "is this a problem", "quick question", "can we do X", "does this need legal review", "take a look for me", or pastes a PM question that needs an instant call (fine / needs review / stop).
Comprehensive toolkit for preparing ISO 13485 certification documentation for medical device Quality Management Systems. Use when users need help with ISO 13485 QMS documentation, including (1) conducting gap analysis of existing documentation, (2) creating Quality Manuals, (3) developing required procedures and work instructions, (4) preparing Medical Device Files, (5) understanding ISO 13485 requirements, or (6) identifying missing documentation for medical device certification. Also use when users mention medical device regulations, QMS certification, FDA QMSR, EU MDR, or need help with quality system documentation.
Enforces JSDoc documentation standards for this TypeScript project. This skill should be used when writing or reviewing TypeScript code to ensure proper documentation with file preambles, function docs, interface docs, and the critical distinction between documenting "what" vs "why". Use this skill to understand the project's JSDoc ESLint rules and established patterns.
Direct REST API access to KEGG (academic use only). Pathway analysis, gene-pathway mapping, metabolic pathways, drug interactions, ID conversion. For Python workflows with multiple databases, prefer bioservices. Use this for direct HTTP/REST work or KEGG-specific control.
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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.