AI-powered code generation for boilerplate, tests, data, and scaffolding

ai-code-reviewer

Design co-learning experiences using the Three Roles Framework (AI as Teacher/Student/Co-Worker). Use when teaching AI-driven development workflows, spec-first collaboration, or balancing AI assistance with foundational learning. NOT for curriculum without AI integration.

Use when collaborating with other AI assistants (Codex, Gemini, Aider, Cursor, OpenCode), delegating tasks, or requesting code review.

Methodology and templates for effective AI consultation workflows with external AI tools like Codex and Gemini.

AI content generation with OpenAI and Claude, callAIWithPrompt usage, prompt storage in app_settings, structured outputs, response format validation, multi-criteria scoring, rate limiting, JSON schema, and AI API best practices. Use when generating content, creating prompts, scoring articles, or working with OpenAI/Claude APIs.

You are a specialized cross-validation assistant that uses Google's Gemini 2.5 Pro API to provide independent, multi-perspective code validation alongside Claude's analysis.

Cross-verify Claude-generated plans and code using OpenAI Codex and Google Gemini CLI. Provides code review, plan validation, and comparative analysis. Use when needing second opinions on Claude's code or plans, validating technical decisions, or seeking consensus from multiple AI models.

Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts. Use when you need to analyze datasets, perform statistical tests, create visualizations, or build predictive models with reproducible, code-based workflows.

Data pipelines, feature stores, and embedding generation for AI/ML systems. Use when building RAG pipelines, ML feature serving, or data transformations. Covers feature stores (Feast, Tecton), embedding pipelines, chunking strategies, orchestration (Dagster, Prefect, Airflow), dbt transformations, data versioning (LakeFS), and experiment tracking (MLflow, W&B).

<skill>

This skill should be used when writing, reviewing, or refactoring documentation that will be consumed as AI context. Optimizes documentation for LLM comprehension using principles of completeness, efficiency, and zero fluff—replacing prose with structured data, enforcing heading hierarchy, detecting meta-commentary, and validating that examples serve a purpose.

Build production-ready LLM applications, advanced RAG systems, and

In traditional software, inputs and outputs are defined. In AI, inputs and outputs are fuzzy. Evals (evaluations) are the "unit tests" for AI products. They allow you to move from "vibes-based" develo

Create an AI Evals Pack (eval PRD, test set, rubric, judge plan, results + iteration loop). Use for LLM evaluation, benchmarks, rubrics, error analysis/open coding, and ship/no-ship quality gates for AI features.

Operational patterns for LLM inference: latency budgeting, tail-latency control, caching, batching/scheduling, quantization/compression, parallelism, and reliable serving at scale. Emphasizes production-grade performance, cost control, and observability.

Guide for AI Agents and LLM development skills including RAG, multi-agent systems, prompt engineering, memory systems, and context engineering.

End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining).

Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptive forecasting.

A production-ready pattern for integrating AI models (specifically Google Gemini) with automatic fallback, retry logic, structured output via Zod schemas, and comprehensive error handling. Use when integrating AI/LLM APIs, need automatic fallback when models are overloaded, want type-safe structured responses, or building features requiring reliable AI generation.

Multimodal AI processing via Google Gemini API (2M tokens context). Capabilities: audio (transcription, 9.5hr max, summarization, music analysis), images (captioning, OCR, object detection, segmentation, visual Q&A), video (scene detection, 6hr max, YouTube URLs, temporal analysis), documents (PDF extraction, tables, forms, charts), image generation (text-to-image, editing). Actions: transcribe, analyze, extract, caption, detect, segment, generate from media. Keywords: Gemini API, audio transcription, image captioning, OCR, object detection, video analysis, PDF extraction, text-to-image, multimodal, speech recognition, visual Q&A, scene detection, YouTube transcription, table extraction, form processing, image generation, Imagen. Use when: transcribing audio/video, analyzing images/screenshots, extracting data from PDFs, processing YouTube videos, generating images from text, implementing multimodal AI features.

Crawl the latest AI-related news from multiple websites, merge and deduplicate them, select 10 in descending order of time, unify summaries into Chinese, and write to a JSON file.

Design AI-powered immersive NPC systems for escape room games using proven actor techniques from Korean immersive escape rooms (Danpyeonsun, Ledasquare). Implements adaptive dialogue, emotional simulation, player profiling, and trust dynamics using Gemini/GPT-4. Creates character profiles with lying probabilities, improvisational responses, and cost-optimized streaming. Use for murder mystery NPCs, suspect interrogation, or dynamic character interactions.

Multi-AI engineering loop orchestrating Claude, Codex, and Gemini for comprehensive validation. USE WHEN (1) mission-critical features requiring multi-perspective validation, (2) complex architectural decisions needing diverse AI viewpoints, (3) security-sensitive code requiring deep analysis, (4) user explicitly requests multi-AI review or triple-AI loop. DO NOT USE for simple features or single-file changes. MODES - Triple-AI (full coverage), Dual-AI Codex-Claude (security/logic), Dual-AI Gemini-Claude (UX/creativity).

Multi-model AI collaboration via orchestrator MCP. Use when seeking second opinions, debugging complex issues, building consensus on architectural decisions, conducting code reviews, or needing external validation on analysis.

ai-output-validation

name: ai-pair-programming

In the era of LLMs, product development moves from writing static specifications to defining "correctness" through Evals. Since models are stochastic, you cannot "fix a bug" with a single line of code

Operational prompt engineering for production LLM apps: structured outputs (JSON/schema), deterministic extractors, RAG grounding/citations, tool/agent workflows, prompt safety (injection/exfiltration), and prompt evaluation/regression testing. Use when designing, debugging, or standardizing prompts for Codex CLI, Claude Code, and OpenAI/Anthropic/Gemini APIs.

Add rules or skills adapters for a new AI tool and wire config, CLI, completion, and tests.

Integrate Vercel AI SDK applications with You.com tools (web search, AI agent, content extraction). Use when developer mentions AI SDK, Vercel AI SDK, generateText, streamText, or You.com integration with AI SDK.

Manages AI SDK model configurations - updates packages, identifies missing models, adds new models with research, and updates documentation

Vercel AI SDK tool patterns for dx-toolkit - input schemas for smart queries, API key handling, raw response returns

ai-sdk-ui

Enterprise AI security - OWASP LLM Top 10, prompt injection defense, guardrails, PII protection

Google AI tools integration. Modules: Gemini API (multimodal: audio/image/video/PDF, 2M context), Gemini CLI (second opinions, Google Search, code review), NotebookLM (source-grounded Q&A). Capabilities: transcription, OCR, video analysis, image generation, web search, document queries. Actions: transcribe, analyze, extract, generate, query, search with Google AI. Keywords: Gemini, Gemini API, Gemini CLI, NotebookLM, audio transcription, image captioning, video analysis, PDF extraction, Google Search, second opinion, source-grounded, multimodal, web research. Use when: processing media files, needing second AI opinion, searching current web info, querying uploaded documents, generating images.

MANDATORY verification system that prevents Claude Code instances from making false claims or fabricating evidence. Enforces cryptographic verification, real testing evidence, and automatic claim validation before any success statements can be made.

Use AI to compare rendered HTML to original PDF page. AI makes contextual judgment about visual accuracy with explainable reasoning. BLOCKING quality gate - stops pipeline if score below 85%.

Comprehensive AI writing detection patterns and methodology. Provides vocabulary lists, structural patterns, model-specific fingerprints, and false positive prevention guidance. Use when analyzing text for AI authorship or understanding detection patterns.

Create AI/BI dashboards. CRITICAL: You MUST test ALL SQL queries via execute_sql BEFORE deploying. Follow guidelines strictly.

aico-code-review

aico-frontend-plan

aico-subagent-driven

Cross-agent communication system for AI workflows. Check messages at session start, send notifications to other agents, and track multi-agent handoffs with correlation IDs.

Write AILANG code. ALWAYS run 'ailang prompt' first - it contains the current syntax rules and templates.

Setup and use Docker AI (Gordon) for intelligent container operations

Generate Apache Airflow ETL pipelines for government websites and document sources. Explores websites to find downloadable documents, verifies commercial use licenses, and creates complete Airflow DAG assets with daily scheduling. Use when user wants to create ETL pipelines, scrape government documents, or automate document collection workflows.

Airoha Technology (MediaTek subsidiary) MPN encoding patterns, suffix decoding, and handler guidance. Use when working with Airoha Bluetooth audio SoCs or AirohaHandler.

Debug and implement Airtable synchronization logic including duplicate prevention, cache management, change detection, and RLS considerations; use when debugging sync failures, stale cache issues, or implementing new Airtable sync features

Use the aissist CLI tool for personal goal tracking, todo management, daily history logging, context-specific notes, guided reflections, and AI-powered semantic recall. Activate when users mention goals, tasks, todos, progress tracking, journaling, work history, personal assistant, meal planning, fitness tracking, or want to search their past activities and reflections.