This skill should be used when the user says "arness code plan", "arn-code-plan", "plan this", "write a plan", "create plan", "implementation plan", "plan feature", "plan the spec", "plan from spec", "generate plan", "arness code plan FEATURE_X", "plan the bugfix", "plan bugfix", "make a plan", or wants to generate an implementation plan from a Arness specification. The skill invokes the arn-code-feature-planner agent to generate the plan, presents it for review, and iterates on user feedback until approved. Produces a PLAN_PREVIEW file that feeds into /arn-code-save-plan.

This skill should be used when the user says "assessing", "arness assessing", "assess", "assess codebase", "technical review", "codebase assessment", "find improvements", "what should I improve", "tech debt review", "pattern compliance check", "codebase health check", "improvement plan", "review my codebase", "what needs fixing", "code quality check", "audit my code", "run an assessment", "arn-assessing", or wants a comprehensive technical assessment of the codebase against stored patterns followed by prioritized improvement execution. Chains to arn-implementing if improvements are identified.

This skill should be used when the user says "execute task N", "run task N", "implement task N", "re-run task N", "retry task N", "run single task", or wants to execute a single specific task from the task list with optional review. This is for ONE task only — for executing the full plan (all tasks), use arn-code-execute-plan instead.

Create or update the project skill registry. Trigger: update skills, skill registry, actualizar skills, or after skill changes.

Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.

Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

**UTILITY SKILL** — Mermaid diagrams for inline markdown: flowcharts, sequence, Gantt, class, state, ER. WHEN: "mermaid flowchart", "sequence diagram", "Gantt chart", "state diagram", "ER diagram", "inline markdown diagram". DO NOT USE FOR: Azure-icon architecture diagrams (drawio), WAF/cost charts (python-diagrams).

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

Meme token fast-trading assistant with two core capabilities: 1. Meme Rush - Real-time meme token lists from launchpads (Pump.fun, Four.meme, etc.) across new, finalizing, and migrated stages 2. Topic Rush - AI-powered market hot topics with associated tokens ranked by net inflow Use this skill when users ask about new meme tokens, meme launches, bonding curve, migration status, pump.fun tokens, four.meme tokens, fast meme trading, market hot topics, or trending narratives.

Query Binance fiat payment capabilities — supported countries, currencies, payment methods, limits, and crypto prices — via public APIs, plus authenticated order/payment history lookup. Use whenever users ask about buying or selling crypto with fiat, depositing or withdrawing fiat, fiat-crypto exchange rates, payment options in a specific country, or their fiat order history — even if they don't explicitly mention Binance APIs.

Builds features with A/B testing in mind using Ronny Kohavi's frameworks and Netflix/Airbnb experimentation culture. Use when implementing feature flags, choosing metrics, designing experiments, or building for fast iteration. Focuses on guardrail metrics, statistical significance, and experiment-driven development.

Distinguishes strategic vs tactical work during development using Shreyas Doshi's frameworks and Marty Cagan's empowered teams principles. Use when making architectural decisions, choosing what to build, preventing "product theater", or applying the LNO framework (Leverage, Neutral, Overhead). Helps avoid feature factory and build work that compounds.

Guides Claude from idea to working prototype using frameworks from OpenAI, Figma, and Airbnb. Use when starting new product features, planning MVP scope, making build-vs-buy decisions, or guiding users from concept to shippable prototype. Applies AI-first thinking (Kevin Weil), simplicity forcing functions (Dylan Field), and complete experience design (Brian Chesky).

Drafts executive memos and stakeholder communications using Amazon's 6-pager structure, Stripe's memo format, and SCQA framework. Use when writing board updates, executive summaries, or strategic documents.

Implement dynamic form updates using Turbo Streams and Stimulus. Use when forms need to update fields based on user selections without full page reloads, such as cascading dropdowns, conditional fields, or dynamic option lists.

Implement Rails nested attributes with dynamic add/remove functionality using Turbo Streams and Simple Form. Use when building forms where users need to manage multiple child records (has_many associations), add/remove nested items without page refresh, or create bulk records inline.

Frontend patterns for Rails applications using Slim templates, Stimulus JavaScript framework, CSS with Optics utilities. Use when building views, adding interactivity, styling components, or when the user mentions Slim, Stimulus, JavaScript, CSS, or frontend development.

Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.