Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wentorai/research-pluginsnpx agentmods add skills/wentorai/research-plugins/algorithm-visualizer-guideWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wentorai/research-plugins/algorithm-visualizer-guide)<a href="https://agentmods.dev/skills/wentorai/research-plugins/algorithm-visualizer-guide"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/algorithm-visualizer-guide/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wentorai/research-plugins/algorithm-visualizer-guide"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/algorithm-visualizer-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 63 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium MCP Rug Pull · line 59 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
- medium MCP Rug Pull · line 65 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.02178 |
| Opus 5.5 | $0.00006 | $0.00871 |
| Sonnet 5.5 | $0.00003 | $0.00436 |
| Haiku 4.5 | $0.00002 | $0.00218 |
Grade A, and why
algorithm-visualizer-guide 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Algorithm Visualizer Guide
Overview
Algorithm Visualizer is an interactive online platform with over 48K stars on GitHub that allows researchers, educators, and students to visualize algorithms through animated graphical representations. The platform provides a web-based environment where algorithm code runs step-by-step alongside a visual canvas that shows data structures being manipulated in real time.
For academic researchers, Algorithm Visualizer serves two primary purposes. First, it is an excellent tool for teaching computational methods in courses and workshops. Complex algorithms in sorting, graph theory, dynamic programming, and numerical methods become immediately intuitive when students can see the step-by-step execution animated on screen. Second, researchers developing new algorithms can use the platform to debug, validate, and communicate their approaches visually, making it easier to explain novel computational contributions in papers and presentations.
The platform supports JavaScript-based algorithm implementations and provides a visualization API with tracer objects for arrays, graphs, logs, and custom 2D canvases. Researchers can create custom visualizations of their own algorithms and share them through the platform's public repository or embed them in course materials.
Platform Architecture and Setup
Algorithm Visualizer consists of three main components that work together to provide the interactive visualization experience.
Components
- algorithm-visualizer - The web application frontend (React-based)
- server - The backend API that compiles and executes code
- algorithms - The public repository of contributed algorithm visualizations
Running Locally for Research Use
# Clone the repository
git clone https://github.com/algorithm-visualizer/algorithm-visualizer.git
cd algorithm-visualizer
# Install dependencies
npm install
# Start development server
npm start
# Access at http://localhost:3000
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.
- 1mo ago First seen · 260 lines · 15 tokens per session scan A 526cf479b672
algorithm-visualizer-guide is a skill published in the GitHub repository wentorai/research-plugins (302 stars, last pushed 4mo ago), licensed MIT. It adds 15 tokens to every session and 2,178 once invoked, about $0.0001 per session on Opus 5.5. 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.
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