data-structure-visualization

A visual study aid for data structures and algorithms, including ways to organize, search, and process data. It can support interactive HTML explanations and step-by-step simulations.

In plain words
What is it for?
Use it to study trees, graphs, sorting, searching, hashing, recursion, complexity, algorithm hand simulations, and data-structure review.
Why use it?
It helps learners follow operations that are difficult to picture, such as how a tree changes or how a sorting algorithm compares items.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/mingchen666/reviva/data-structure-visualization
Any agent
npx skills add mingchen666/Reviva --skill data-structure-visualization
Clone the repo
git clone --depth 1 https://github.com/mingchen666/Reviva

Made for: Claude Code, Codex.

Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 947 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00059 $0.00947
Opus 5 $0.00030 $0.00474
Sonnet 5 $0.00012 $0.00189
Haiku 4.5 $0.00006 $0.00095

Measured 2d ago against content hash d0f8c8d2e0ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

data-structure-visualization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

electron/builtin-assets/skills/data-structure-visualization/SKILL.md · 90 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 90 lines · 59 tokens per session scan A d0f8c8d2e0ef

Subscribe to this mod's changes

data-structure-visualization is a skill published in the GitHub repository mingchen666/Reviva (217 stars, last pushed 6d ago), with no licence file. It adds 59 tokens to every session and 947 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

beautiful-article

把用户提供的素材(网页 URL / PDF / DOCX / Markdown / 纯文本 / 截图 / 粘贴材料)编辑、设计成一篇美丽的、可离线打开和分享的单文件 HTML 网页文章。基于 reacticle 组件协议:不手写裸 HTML/CSS,而用语义组件 + 受主题约束的 Raw 自由层;按 source→规划→双确认→生成→终审→修复的小型 harness 流程推进,默认 100% 信息保留的长文。触发场景:把 URL/PDF/DOCX/文章做成网页文章 / 长文 / briefing / 解释文 / 视觉文章 / 教程 / 审阅复盘 / 方案分析,'render this as a beautiful web…

ConardLi/garden-skills · 226 tokens

web-design-engineer

Build or redesign polished browser-rendered visual artifacts with HTML/CSS/JavaScript/React: pages, dashboards, prototypes, slide decks, animations, UI mockups, and data visualizations. Use for visual front-end creation, design-system exploration, design critique, or explicit browser acceptance / QA of a web artifact.…

ConardLi/garden-skills · 96 tokens

gpt-image-2

面向 GPT Image 2 的图像生成 / 编辑技能。可在 3 种环境下使用:(A) Garden 本地模式,通过 OpenAI 兼容接口直接出图并落盘;(B) Host-Native 模式,把本 Skill 当作提示词工程指引,把渲染好的 prompt 交给宿主 Agent 自带的图像工具出图;(C) Advisor 模式,宿主无任何图像工具时退化为高质量 prompt 顾问。涵盖 18 大类、80+ 个结构化模板,覆盖海报 / UI / 产品 / 信息图 / 学术图 / 技术架构图 / 漫画 / 头像 / 流程板 / 电影分镜 / IP 周边 / 编辑工作流等场景。.

ConardLi/garden-skills · 177 tokens

kb-retriever

面向本地知识库目录的检索和问答助手。核心流程:(1)分层索引导航 (2)遇到PDF/Excel时必须先读取references学习处理方法 (3)处理文件后再检索。按文件类型组合使用 grep、Read、pdfplumber、pandas 进行渐进式检索,避免整文件加载。用户问题涉及"从知识库目录回答问题/检索信息/查资料"时使用。.

ConardLi/garden-skills · 105 tokens

wegent-knowledge

Knowledge base management and search tools for Wegent. Provides capabilities to list, create, update, and search knowledge bases and documents using RAG retrieval. Use this skill when the user wants to manage knowledge bases, documents, or search for information programmatically.

wecode-ai/Wegent · 51 tokens

web-video-presentation

把一篇文章或口播稿,做成"看起来像视频"的点击驱动 16:9 网页演示,可选合成口播音频。流程:原始文章 → 一次产出口播稿 + outline 开发计划 → 用户一次对齐 5 件事(稿子 / outline / 主题 / 素材 / 开发模式)→ 网页开发(逐章 / 顺序 / 并行)→ 可选音频合成(provider-agnostic:内置 MiniMax mmx-cli + OpenAI TTS,可换 ElevenLabs / edge-tts / Azure / 自带 TTS)。outline 只规划节奏与信息密度,不规划动画 —— 动画由章节开发时按 PRINCIPLES + ANTI-AI…

ConardLi/garden-skills · 314 tokens