algorithmic-art
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Install with Tessl CLI
npx tessl i github:haniakrim21/everything-claude-code --skill algorithmic-art74
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly defines its purpose (algorithmic art with p5.js), includes specific techniques and capabilities, and provides explicit trigger guidance. The description uses proper third-person voice and includes relevant natural language terms users would employ. The addition of the copyright constraint adds helpful context for appropriate use.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration.' Mentions specific techniques like flow fields and particle systems. | 3 / 3 |
Completeness | Clearly answers both what (creating algorithmic art with p5.js, seeded randomness, interactive parameters) AND when (explicit 'Use this when...' clause with specific trigger scenarios). Also includes a constraint about avoiding copyright violations. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'art using code', 'generative art', 'algorithmic art', 'flow fields', 'particle systems'. These are terms users would naturally use when requesting this type of work. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche with distinct triggers: specifically targets p5.js algorithmic/generative art with named techniques (flow fields, particle systems). Unlikely to conflict with general coding or other art skills due to specific domain focus. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a creative framework for generative art but suffers from extreme verbosity and redundancy. The philosophical approach is interesting but the document spends too much space on abstract concepts Claude already understands while lacking concrete, executable implementation guidance. The workflow is present but missing validation steps critical for ensuring generated artifacts work correctly.
Suggestions
Reduce content by 60-70% by removing redundant emphasis on 'craftsmanship' and 'mastery', eliminating explanations of basic concepts, and trusting Claude to understand algorithmic art principles
Move the philosophy examples and implementation patterns to separate reference files (e.g., PHILOSOPHY_EXAMPLES.md, PATTERNS.md) to improve progressive disclosure
Add concrete validation steps: 'Test artifact loads in browser', 'Verify seed produces identical output', 'Check all UI controls update canvas'
Replace abstract guidance ('think about what the philosophy demands') with executable code templates showing complete, working implementations
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~400 lines with significant redundancy. Concepts like 'meticulously crafted' and 'master-level' are repeated excessively as instructed within the skill itself. Many sections explain obvious concepts (what algorithmic art is, how to think about parameters) that Claude already understands. | 1 / 3 |
Actionability | Contains some executable code snippets (seeded randomness, canvas setup) but most guidance is abstract philosophy rather than concrete implementation. The code examples are incomplete fragments rather than copy-paste ready solutions. Heavy reliance on reading external template files rather than providing inline executable examples. | 2 / 3 |
Workflow Clarity | The two-step process (philosophy creation → implementation) is clearly stated, and Step 0 emphasizes reading the template first. However, validation checkpoints are missing - there's no guidance on how to verify the generated art works correctly, no error recovery steps, and no feedback loops for iterating on the output. | 2 / 3 |
Progressive Disclosure | References external files appropriately (templates/viewer.html, templates/generator_template.js) with clear signaling. However, the main SKILL.md itself is a monolithic wall of text with excessive inline content that could be split into separate reference files (philosophy examples, implementation patterns, UI requirements). | 2 / 3 |
Total | 7 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.