Skill UI

This skill ensures browser automation reliability by anchoring actions to stable DOM selectors and semantic roles rather than screen coordinates. It helps workflows survive layout shifts, A/B tests, and viewport changes. Users should inspect the DOM, prioritize data-testid attributes, verify selectors match exactly one element, and wait on state instead of fixed time. It includes error handling for modals and navigation races.

Shared vocabulary and principles for designing deep modules with small interfaces, clean seams, and testable, AI-navigable codebases.

Analyzes Claude Code and Codex usage logs to surface cost drivers such as low cache hit rates, unpaid cache writes, top-tier sub-agents, reasoning share, and bloated sessions, with evidence and what-if savings to help cut AI coding spend.

This tool provides a unified cost view for AI agents like Claude Code, Codex, and Grok. It reads local logs to calculate spend, token usage, and cache hit ratios per provider and model. It flags unpriced models and supports filtering by time range, project, and provider. Output can be JSON or Markdown. All data stays local, ensuring privacy. Ideal for auditing AI usage costs and comparing provider pricing.

Calculate the cost per million tokens for running AI models locally on your own hardware like Ollama or llama.cpp. It factors in electricity prices, hardware costs, power consumption, and generation speed to determine the break-even point against hosted API models. Useful for deciding whether to deploy models locally or use cloud services based on actual usage and financial constraints.

A disciplined approach for diagnosing hard bugs and performance regressions. This skill guides users to build tight feedback loops, reproduce issues, and minimize scenarios before hypothesizing. It emphasizes redacting secrets, creating deterministic tests, and avoiding premature assumptions. Use when debugging complex failures or performance issues in software development.

Answer factual and how-to questions about Nightingale (n9e) platform including UI navigation, business groups, subscription rules, notification pipeline, categraf plugin fields, metric names, config syntax, and source code implementation details. Uses official docs and embedded source code corpus as evidence sources.

Reviews AI-assisted Word/DOCX workflows for operational integrity before professional reliance: preserves originals, tracked changes, comments, numbering, sections, edit identity, structure, save/verify cycles, and human acceptance; returns PASS, REVIEW, or BLOCK.

Actively build and sharpen a project's domain model by challenging terminology, recording glossary terms, and writing ADRs when decisions are hard to reverse and surprising.

This skill statically inspects local JavaScript, Electron, native binary, .NET, and CUDA applications to explain feature functionality with file and line evidence. It supports analyzing packaged .asar files, ELF/PE binaries, EVM bytecode, and CUDA programs without execution. Users must be authorized to study the target. It helps understand or reimplement features safely by parsing code and metadata, refusing requests to bypass security mechanisms or DRM.

This skill coordinates work across a RuFlo AI-agent swarm by discovering channels, reading signed updates, and checking claims. It helps manage multi-agent status, handoffs, ownership conflicts, and shared-work planning. Users must treat relay-sourced messages as untrusted and avoid irreversible actions unless explicitly requested. It ensures safe coordination without unauthorized state changes.

This skill involves escalating a disputed refund case to the billing lead. Collect the order number and customer reason, then page the billing lead to inform them. This ensures proper handling of financial disagreements and maintains accurate billing records.