---
name: algorithm-visualizer-6aaedd49563b
description: Generate visual representations of algorithm execution
allowed-tools:
  - Bash
  - Read
  - Write
  - Grep
  - Glob
graph:
  domains: [domain:computer-science]
  specializations: [specialization:algorithms-optimization]
  skillAreas: [skill-area:dynamic-programming, skill-area:graph-algorithms, skill-area:data-visualization]
  roles: [role:backend-engineer, role:computational-scientist]
---

# Algorithm Visualizer Skill

## Purpose

Generate visual representations of algorithm execution to aid understanding, debugging, and explanation of algorithmic concepts.

## Capabilities

- Step-by-step execution visualization
- Data structure state visualization
- Graph algorithm animation
- DP table visualization
- Generate animated GIFs/videos
- Interactive visualization generation
- Tree and array state rendering

## Target Processes

- algorithm-implementation
- dp-pattern-matching
- graph-traversal
- interview-problem-explanation

## Visualization Types

1. **Array Operations**: Sorting, searching, two-pointer techniques
2. **Tree Structures**: Binary trees, BST operations, tree traversals
3. **Graph Algorithms**: BFS, DFS, shortest paths, MST
4. **DP Tables**: State transitions, optimal substructure
5. **Data Structures**: Stack, queue, heap operations

## Input Schema

```json
{
  "type": "object",
  "properties": {
    "algorithm": { "type": "string" },
    "input": { "type": "object" },
    "format": {
      "type": "string",
      "enum": ["ascii", "svg", "gif", "html"]
    },
    "steps": { "type": "boolean", "default": true }
  },
  "required": ["algorithm", "input"]
}
```

## Output Schema

```json
{
  "type": "object",
  "properties": {
    "success": { "type": "boolean" },
    "visualization": { "type": "string" },
    "steps": { "type": "array" },
    "format": { "type": "string" }
  },
  "required": ["success"]
}
```

## Integration

Can integrate with visualization libraries like Manim, D3.js, or generate ASCII art for terminal-based visualization.


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Content & Media, Data & Analytics, Design, Development & Engineering, Education & Research
Roles: Data Scientist, Frontend Developer, Researcher, Technical Writer, UX Designer
Specialties: API, Cross Platform, Frontend
Tools: Manim, D3.Js
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: ed2cfe55bc83f8bc7c3eceec11bd8dbd46a73ed8cdc7cc6c68346229536ad85b