Expert guidelines for Ethereum smart contract development with Solidity, OpenZeppelin, and Hardhat

Use when decisions could affect groups differently and need to anticipate harms/benefits, assess fairness and safety concerns, identify vulnerable populations, propose risk mitigations, define monitoring metrics, or when user mentions ethical review, impact assessment, differential harm, safety analysis, vulnerable groups, bias audit, or responsible AI/tech.

Designs and implements Extract, Transform, Load pipelines for data processing

Apache Airflow, dbt, Prefect, Dagster, and modern data orchestration for production data pipelines

Analyze evaluation baseline results, identify failure patterns, and generate actionable insights. Use after running eval baselines or when user asks to analyze eval results, check benchmarks, investigate failures, or understand what's failing.

Evaluation framework patterns for RAG and LLMs, including faithfulness metrics, synthetic dataset generation, and LLM-as-a-judge patterns. Triggers: ragas, deepeval, llm-eval, faithfulness, hallucination-check, synthetic-data.

Find AILANG vs Python eval gaps and improve prompts/language. Use when user says 'find eval gaps', 'analyze benchmark failures', 'close Python-AILANG gap', or after running evals.

Review diff classification cases to determine if the LLM correctly categorized hunks, identified change type, and told a coherent story.

EvalKit is a conversational evaluation framework for AI agents that guides you through creating robust evaluations using the Strands Evals SDK. Through natural conversation, you can plan evaluations, generate test data, execute evaluations, and analyze results.

Use when user references architecture principles, at start of fresh conversation with design work, before creating any requirements/design/implementation documents, or when reviewing for compliance - grounds problem framing and solution making in all 9 principle categories using citation-manager to extract full context

Evaluate RAG systems with hit rate, MRR, faithfulness metrics and compare retrieval strategies. Use when testing retrieval quality, generating evaluation datasets, comparing embeddings or retrievers, A/B testing, or measuring production RAG performance.

Use when need explicit quality criteria and scoring scales to evaluate work consistently, compare alternatives objectively, set acceptance thresholds, reduce subjective bias, or when user mentions rubric, scoring criteria, quality standards, evaluation framework, inter-rater reliability, or grade/assess work.

Evaluate TappsCodingAgents framework effectiveness and provide continuous improvement recommendations. Use for analyzing usage patterns, workflow adherence, and code quality metrics.

Comprehensive EVE Online project management and ESI integration toolkit. Use when updating, auditing, or integrating ESI into EVE Online projects like EVE_Rebellion, EVE_Gatekeeper, EVE_Ships, or any EVE-related development. Triggers on project updates, ESI integration, compliance checking, asset management, or multi-project coordination.

Structure systems around asynchronous, event-based communication to decouple producers and consumers for improved scalability and resilience. Use when building loosely coupled systems with asynchronous message-based communication.

Add new events to Bob The Skull's event-driven architecture. Use when creating new events, event publishers, event handlers, or extending the event system with new event types.

JSONL event stream for external integrations and hooks

Use when generating branded QR codes for ProductTank SF events - speaker LinkedIn profiles, sponsor websites, or Slack join links. Handles single/bulk generation, correct logo mapping, GDrive upload, and mandatory test-scanning.

Create new event scraping scripts for websites. Use when adding a new event source to the Asheville Event Feed. ALWAYS start by detecting the CMS/platform and trying known API endpoints first. Browser scraping is NOT supported (Vercel limitation). Handles API-based, HTML/JSON-LD, and hybrid patterns with comprehensive testing workflows.

Event sourcing patterns and design decisions

Event-driven design conventions: event envelope, naming, versioning, schema evolution rules, idempotency, ordering/partitioning, retry and dead-letter handling

Implements Clix event tracking (Clix.trackEvent) with consistent naming, safe

AWS EventBridge serverless event bus for event-driven architectures. Use when creating rules, configuring event patterns, setting up scheduled events, integrating with SaaS, or building cross-account event routing.

Use when spec and code diverge - AI analyzes mismatches, recommends update spec vs fix code with reasoning, handles evolution with user control or auto-updates

Search for relevant code snippets, examples, and documentation from billions of GitHub repositories, documentation pages, and Stack Overflow posts. Use this skill when coding tasks require real working code examples, API usage patterns, framework setup instructions, or library implementation details to eliminate hallucinations and provide accurate, token-efficient context.

Retrieve and extract content from URLs with AI-powered summarization and structured data extraction. Use for scraping web pages, extracting specific information, summarizing articles, or crawling websites with subpages.

Process CSV data files by cleaning, transforming, and analyzing them. Use this when users need to work with CSV files, clean data, or perform basic data analysis tasks.

Provides three production-ready ML training examples (sentiment classification, text generation, RedAI trade classifier) with complete training scripts, deployment configs, and datasets. Use when user needs example projects, reference implementations, starter templates, or wants to see working code for sentiment analysis, text generation, or financial trade classification.

Tests marketplace visibility configurations and catalog tiers (preview catalog only)

Analyze mock data and examples for cultural assumptions, understanding what they communicate about who the product is for. Use when reviewing test data, documentation, or seed data.

A skill for generating Excalidraw-format diagrams from natural language descriptions. This skill helps create visual representations of processes, systems, relationships, and ideas without manual draw

Generate architecture diagrams as .excalidraw files from codebase analysis. Use when the user asks to create architecture diagrams, system diagrams, visualize codebase structure, or generate excalidraw files.

Push Excel data back to BIM models. Update parameters, properties, and attributes from structured spreadsheets.

Excel Translation Skill

Measure quality. Descend toward excellence. No binary gates—only vectors.

Guide for creating exceptions using fastapi-problem that are automatically converted to RFC 9457 Problem Details responses.

Use when implementing exchange rate functionality - provides complete patterns for fetching BTC/fiat exchange rates from Coinbase API, caching strategies, conversion utilities, and React hooks for displaying rates in UI

Deploy a Vibes app to exe.dev VM hosting. Uses nginx on persistent VMs with SSH automation. Supports client-side multi-tenancy via subdomain-based Fireproof database isolation.

Create or resume an execution plan - a design document that a coding agent can follow to deliver a working feature or system change

shannon-execution-verifier

Use to systematically validate documents, stories, or processes against defined checklists. Ensures quality and completeness.

Execute one feature (FEAT-XXX) at a time using docs/forge/ideas/<IDEA_ID>/latest/tasks.md as the source of truth. Creates a short workspace checklist and tracks progress so reruns continue automatically.

<objective>

The ONLY way to interact with existing projects. Load when user references ANY project by name, ID, or number. Includes: continue, resume, status, progress, check, review, work on [existing project]. NEVER read project files directly.

Execute approved task specifications sequentially with TDD, comprehensive testing, and validation. This skill should be used for implementing tasks from approved specs with full audit trail.

This skill should be used when executing tasks from ai-state/active/tasks.yaml sequentially. It loads tasks, gathers context, implements features with phase-appropriate testing, updates task status in tasks.yaml, organizes tests into ai-state/regressions/ folders, and logs all operations to operations.log. Use after write-plan creates tasks.yaml or when resuming development work.

Complete development lifecycle for GitHub/local issues - branch, implement, test, PR, merge with quality gates