Claude Skills by aicodedecode

Use when working with WP-CLI (wp) for WordPress operations: safe search-replace, db export/import, plugin/theme/user/content management, cron, cache flushing, multisite, and scripting/automation with wp-cli.yml.

Use when building UIs leveraging the WordPress Design System (WPDS) and its components, tokens, patterns, etc.

Create new agent skills with proper structure, progressive disclosure,

Use when writing a complete SEO article. Includes the full anti-AI-slop ruleset (banned vocabulary, banned phrases, banned structural patterns) and voice rules. The agent researches the SERP itself if needed — no keyword data exports required.

Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.

Review docs/prose for Writing Guidelines compliance. Use when asked to "review my docs", "check writing style", "audit prose", "review docs voice and tone", or "check this page against the writing handbook".

This skill should be used when the user asks to "create a hookify rule", "write a hook rule", "configure hookify", "add a hookify rule", or needs guidance on hookify rule syntax and patterns.

Write, rewrite, or review Russian and English prose so it reads as written by a person, not a model. Use for requests to make text more human, simplify language, remove formulaic writing, or edit articles, notes, docs, UI copy, presentations, and Figma text. Covers drafting and language review without a separate editing skill. Also use when the user corrects the agent's wording, says how they write or how their product speaks, or asks to remember a writing preference.

Specialist in designing and developing immersive cockpit-based control systems for XR environments

Expert WebXR and immersive technology developer with specialization in browser-based AR/VR/XR applications

Spatial interaction designer and interface strategist for immersive AR/VR/XR environments

This skill should be used when the user asks to "test for XSS vulnerabilities", "perform cross-site scripting attacks", "identify HTML injection flaws", "exploit client-side injection vulnerabilities", "steal cookies via XSS", or "bypass content security policies". It provides comprehensive techniques for detecting, exploiting, and understanding XSS and HTML injection attack vectors in web applications.

Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).

Runs a disciplined Discuss -> Map -> Decompose -> Execute -> Verify loop

Master 1Password: vaults, Watchtower, passkeys, SSH agent, CLI, and family/team administration. Use when getting full value from 1Password personally or administering it for others.

Create 3D visuals with modeling, texturing, lighting, rendering, and optimization for web and product.

Create 3D web experiences: scene setup, models, materials, lighting, animation, scroll-driven scenes, and performance budgets. Use when adding 3D to websites beyond basic demos.

Writing abstracts that get papers read — structured content, the 5-sentence core, and journal-specific constraints.

Learn effectively from courses and academies: choosing programs, studying actively, and converting courses into skills. Use when investing time/money in structured learning.

Audit designs for accessibility with WCAG checklists covering color, type, focus, motion, and content.

Run ABM programs — target account selection, personalized campaigns, sales orchestration, and account-level measurement.

Label smarter, not more — pick the most informative examples for annotation to maximize model gains per label.

Optimize content for AI answer engines (AEO/GEO): citation-friendly structure, factual precision, and measuring AI visibility. Use when AI search drives discovery.

Measuring emotion from behavior and physiology — facial expression, voice, EDA, and self-report integration.

Build and run affiliate programs — recruitment, commission structures, partner enablement, and fraud prevention.

Evaluate AI agents rigorously — task benchmarks, success criteria, failure taxonomy, cost/latency tracking, and regression testing. Use when you need to know whether an agent actually works, not whether it demos well.

Manage fleets of local AI agents: lifecycle, monitoring, task assignment, and resource control. Use when running multiple CLI agents via an orchestrator like AI Maestro.

Manage fleets of local AI agents — spawn, supervise, route tasks, monitor progress, and shut down workers cleanly. Use when coordinating multiple agents on parallel workstreams.

Architect persistent, searchable memory for agents — episodic, semantic, and procedural stores with retrieval, consolidation, and forgetting policies. Use when designing how an agent remembers across sessions.

Design memory for AI agents — short-term context, long-term stores, retrieval strategies, and memory-augmented reasoning. Use when an agent must remember facts, learn preferences, or stay coherent across sessions.

Coordinate agents via messaging: send, receive, and manage inter-agent communication. Use when agents need to collaborate, hand off work, or notify each other.

Orchestrate agents at runtime — task routing, scheduling, parallel execution, result aggregation, and supervision dashboards. Use when running agents as a managed fleet rather than one-off calls.

Design tools for AI agents — clean function interfaces, typed schemas, informative errors, idempotency, and tool documentation. Use when giving an agent new capabilities or fixing flaky tool use.

Build reusable agent workflow patterns — subagents with scoped briefs, event hooks, slash commands, and session management. Use when turning one-off agent tasks into repeatable, composable workflows.

Run goal-driven autonomous agent loops — decomposing objectives, executing tool chains, self-critiquing, and iterating until done. Use when exploring what fully autonomous task execution looks like and its limits.

Coordinate teams of role-based agents — role definitions, task delegation, sequential and hierarchical workflows, and shared memory. Use when a job naturally splits into specialist roles collaborating.

Build LLM applications with chain-style orchestration frameworks — prompts, chains, tool-calling agents, memory, and retrieval pipelines. Use when structuring multi-step LLM programs, adding tools to a model, or composing RAG systems in code.

Build data-centric LLM applications with indexing and retrieval frameworks — document ingestion, indices, query engines, and RAG pipelines. Use when the core problem is getting the right data in front of the model.

Build agents on OpenAI's platform patterns — assistants-style threads, function calling, structured outputs, and multi-step tool workflows. Use when working with OpenAI models as the agent engine.

AI agent guidance — agent architecture, tool design, planning loops, guardrails, evaluation, and production agents.

Architect autonomous agent systems — perception/action loops, tool design, planning strategies, memory, and multi-agent orchestration patterns. Use when designing an agent from scratch or scaling a prototype to production.

Design and build LLM agents: ReAct loops, tool schemas, planning, memory, guardrails, evals, and human-in-the-loop. Use when building autonomous multi-step AI systems.

Build AI chatbots end to end — conversation design, persona, retrieval grounding, escalation, and deployment. Use when creating a chatbot for support, sales, or internal assistance.

Ship AI features to production — model selection, evals, latency/cost optimization, guardrails, monitoring, and iteration loops. Use when turning an LLM prototype into a reliable product feature.

Craft effective AI image prompts with structured syntax, style control, and iterative refinement techniques.

Practice AI safety across the lifecycle — risk assessment, alignment concepts, evaluation, deployment safeguards, and governance. Use when building or deploying AI systems responsibly.

Build streaming AI user interfaces with AI SDK patterns — message rendering, tool-call displays, loading states, and optimistic updates. Use when creating chat UIs that stream model output and show agent activity.

Generate UI with AI tools effectively: prompt structure, design-system grounding, iteration technique, and evaluating output quality. Use when using AI to create interfaces.

Build with AI21 Labs' models — Jurassic for generation and strong task-specific models for enterprise use.

Distinguishing aims, objectives, hypotheses, and milestones — the hierarchy that keeps proposals logically tight.