Use when writing, reviewing, or debugging Terraform/OpenTofu modules, tests, CI, scans, or state ops — diagnoses failure mode (identity churn, secrets, blast radius, CI drift, state corruption) with version-aware guards.

Audit a backlink profile using Ahrefs MCP data: profile health, anchor text distribution, toxic link identification, lost link reclamation, and gap analysis against competitors. Use this skill when reviewing backlink health, scoping a disavow project, recovering from a manual action, planning link building, or doing M&A due diligence on a property's link equity. Triggers on backlink audit, link profile, toxic links, disavow, anchor text analysis, lost links, link reclamation, referring domains, link gap. Also triggers when traffic decline correlates with link loss or when an unnatural link warning appears in Search Console.

Audit content gaps and decay using Ahrefs MCP data: missing topics, thin coverage, outdated content, and decaying pages. Use this skill when planning a content roadmap, refreshing a stale catalog, building topical authority, or identifying which existing pages need update versus replacement. Triggers on content gap, content audit, content refresh, content roadmap, decaying content, content decay, topical authority, what topics should we cover, where is competitor content stronger. Also triggers when organic traffic is flat despite consistent publishing.

Run upstream brand discovery covering audience research, competitive landscape, category dynamics, problem space, and positioning territory exploration. Use this skill at the very start of a brand or website project when the user needs to understand who they're for, who they compete with, what the audience actually needs, and where the brand could plausibly stand. Triggers on brand discovery, audience research, market research, competitive scan, category research, customer research, who is this for, who are we, positioning research, intake, kickoff. Also triggers when a creative brief is requested but the upstream inputs (audience, competitors, problem space) are not yet clear.

Build production-ready frontend components with accessible markup, sensible props, defined states, and tested behavior. Use this skill whenever the user wants to build a component from scratch, refactor an existing one, design a component API, or implement a UI element with proper states and accessibility. Triggers on build a component, create a button, create a modal, create a form input, component API, props design, component states, refactor component, accessible component. Also triggers when implementing UI from a design that needs to be reusable.

Help developers integrate Chainlink VRF into smart contracts. Use for consumer contract generation with VRFConsumerBaseV2Plus, subscription setup and funding (LINK or native), keyHash and gas lane selection, coordinator address lookup and debugging VRF integrations. Trigger on any mention of VRF, verifiable randomness, on-chain random number generation, requestRandomWords, fulfillRandomWords, VRF subscription, VRF coordinator, keyHash, or provably fair randomness in a smart contract, even if the user does not say 'VRF' explicitly.

Validates documentation structural integrity including heading hierarchy, metadata, file naming, navigation, and cross-references. Use when checking documentation organization or validating toctree structure.

Use when authoring an agent skill that wraps a command-line tool — covers hands-on tool exploration, required vs. recommended sections, installation/usage structure, trigger-rich descriptions, task-grouped commands, progressive disclosure, and a pre-publish checklist. Triggers for CLI / command-line / terminal / shell-command tools and binary wrappers; for review, run the Checklist section.

Use when optimizing CLAUDE.md, AGENTS.md, custom commands, or skill files — diagnose the concrete failure first, then apply current documented Anthropic best practices (explicit instructions, context/motivation, examples, output and verbosity control, thinking/effort, CLAUDE.md size and skill-description rules) instead of inventing improvements. Triggers when a prompt isn't followed, a skill won't activate, CLAUDE.md is too long or ignored, or migrating prompts to current Claude models.

Implements React/TypeScript unit, integration, and browser E2E tests with the repository's configured runner, mocks, setup, and browser harness. Use when creating or completing frontend tests and generated test skeletons.

Extends Fastly VCL with loops, functions, constants, macros, conditionals, and includes via XVCL — a VCL transpiler that compiles .xvcl files into standard VCL. Use when writing VCL for Fastly, working with .xvcl files, generating repetitive VCL (multiple backends, routing rules, headers) with loops, defining reusable VCL functions with return values, using compile-time constants instead of magic numbers, or writing any Fastly VCL configuration. XVCL syntax is not in training data so this skill is required. Also applies when writing and testing VCL locally (compile with `uvx xvcl`, test with falco), reducing VCL code duplication, splitting large VCL into modular includes, or doing any VCL development task for Fastly — even without explicitly mentioning XVCL.

Use when challenging ideas, plans, decisions, or proposals. Invoke to play devil's advocate, run a pre-mortem, red team, stress test assumptions, audit evidence quality, or find blind spots before committing. Do NOT use for building plans, making decisions, or generating solutions — this skill only challenges and critiques. For a multi-agent panel that challenges and then commits to a verdict, use the-jury.

When the user wants to launch a product across multiple platforms, plan a Product Hunt launch, build a waitlist, or execute a multi-channel launch strategy. Also use when the user mentions 'product launch,' 'Product Hunt,' 'launch strategy,' 'waitlist,' 'beta launch,' 'BetaList,' 'Hacker News,' 'launch day,' 'AppSumo,' 'multi-channel launch.' This skill covers multi-platform launch execution from pre-launch through post-launch optimization. Do NOT use for technical implementation, code review, or software architecture.

Creates structured Request for Comments (RFC) documents for proposing and deciding on significant changes. Use when the user says "write an RFC", "create a proposal", "I need to propose a change", "draft an RFC", "document a decision", or needs stakeholder alignment before making a major technical or process decision. Do NOT use for TDDs/implementation docs (use technical-design-doc-creator instead), README files, or general documentation.

Expert guide for designing and building high-quality skills from scratch through structured conversation. Use when someone wants to create a new skill, build a skill, design a skill, or asks for help making Agents do something consistently. Also use when someone says "turn this into a skill", "I want to automate this workflow", "how do I teach my Agent to do X", or mentions creating SKILL.md files. Covers standalone skills and MCP-enhanced workflows. Do NOT use for creating subagents (use subagent-creator) or technical design documents (use create-technical-design-doc).

Feature planning and implementation with 4 adaptive phases (Specify, Design, Tasks, Execute). Auto-sizes depth by complexity. Writes testable requirements in EARS notation, atomic tasks, atomic Conventional Commits, and requirement traceability. Ships deterministic Python validation scripts so structural gates are enforced by code, not memory. Features an independent Verifier (author != verifier, evidence-or-zero), a discrimination sensor, a decision log (STATE.md), a test-coverage matrix, and a self-improving lessons layer. Stack-agnostic and tool-agnostic. Use when (1) planning features, (2) implementing with verification and atomic commits, (3) validating an implementation against a spec. Triggers on "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "record decision", "pause work", "resume work". Do NOT use for pure architecture decomposition analysis or standalone technical design documents.

Generate Excalidraw diagrams from natural language descriptions. Outputs .excalidraw JSON files openable in Excalidraw. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", "generate an Excalidraw file", "draw an ER diagram", "create a sequence diagram", or "make a class diagram". Supports flowcharts, relationship diagrams, mind maps, architecture, DFD, swimlane, class, sequence, and ER diagrams. Can use icon libraries (AWS, GCP, etc.) when set up. Do NOT use for code architecture analysis (use the architecture skills), Mermaid diagram rendering (use mermaid-studio), or non-visual documentation (use docs-writer).

When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products. Do NOT use for technical implementation, code review, or software architecture.

AI frontend specialist and design consultant that guides users through a structured discovery process before generating any code. Collects visual references, design tokens, typography, icons, layout preferences, and brand guidelines to ensure the final output matches the user's vision with high fidelity. Use when the user asks to build, design, create, or improve any frontend interface — websites, landing pages, dashboards, components, apps, emails, forms, modals, or any UI element. Also triggers on "build me a UI", "design a page", "create a component", "improve this layout", "make this look better", "frontend", "interface", "redesign", or when the user provides mockups, screenshots, or design references. Do NOT use for backend logic, API design, database schemas, or non-visual code tasks.

Generates abstract invariants using domain abstraction — intervals, octagons, polyhedra, sign domains — to find invariants that concrete reasoning misses. Use when standard invariant inference fails, when the invariant involves relationships between multiple variables, or when verifying numerical code.