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.
56
67%
Does it follow best practices?
Impact
54%
1.80xAverage score across 10 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./docs/v19.7/configuration/agent/skills_external/antigravity-awesome-skills-main/skills/algorithmic-art/SKILL.mdQuality
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 niche in generative/algorithmic art using p5.js. It provides specific capabilities, natural trigger terms, explicit 'Use when' guidance, and a clear constraint about originality. The description is concise yet comprehensive, making it easy for Claude to select appropriately from a large skill set.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and techniques: 'algorithmic art using p5.js', 'seeded randomness', 'interactive parameter exploration', 'flow fields', 'particle systems'. These are concrete, specific capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration) and 'when' (explicit 'Use this when...' clause listing specific trigger scenarios). Also includes a constraint about avoiding copyright violations. | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would actually say: 'art using code', 'generative art', 'algorithmic art', 'flow fields', 'particle systems', and 'p5.js'. Good coverage of how users would phrase requests in this domain. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: p5.js-based algorithmic/generative art. The specific technology (p5.js), techniques (seeded randomness, flow fields, particle systems), and domain (generative art) make it very unlikely to conflict with other skills. | 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 is extremely verbose and repetitive, restating the same concepts about craftsmanship, philosophy-driven implementation, and template usage many times over. While it provides a clear two-phase workflow and references external templates appropriately, the actionability suffers from being more philosophical than concrete - the actual algorithm implementation guidance is abstract. The content would benefit enormously from being cut to roughly 1/3 its current length while moving examples and detailed specifications to referenced files.
Suggestions
Reduce content by at least 60% - eliminate repeated instructions about craftsmanship emphasis, template usage, and Anthropic branding. State each directive once clearly.
Move the five philosophy examples to a separate EXAMPLES.md file and reference it, keeping at most one condensed example inline.
Add concrete validation steps: e.g., 'Open the HTML file in browser and verify: (1) canvas renders, (2) seed navigation works, (3) all parameter sliders update the art in real-time.'
Replace abstract implementation guidance ('express the philosophy through code') with at least one complete, executable p5.js algorithm example showing the full pipeline from philosophy to working code.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~300+ lines with extensive repetition. The same points about 'algorithmic philosophy,' 'craftsmanship,' 'Anthropic branding,' and 'use the template' are repeated 5+ times each. Concepts Claude already understands (what generative art is, how p5.js works, what parameters are) are over-explained. The philosophy examples alone consume significant space repeating the same pattern. | 1 / 3 |
Actionability | Contains some concrete code snippets (seeded randomness, canvas setup, control group HTML) but much of the guidance is abstract and philosophical rather than executable. The actual p5.js algorithm implementation is left entirely vague ('express the philosophy through code'), and the code examples are incomplete fragments or pseudocode-level templates rather than copy-paste ready implementations. | 2 / 3 |
Workflow Clarity | The two-step process (philosophy creation → p5.js implementation) is clearly stated, and there's a numbered creative process at the end. However, there are no validation checkpoints - no step to verify the HTML works, no validation of the generated art, no error recovery steps. The workflow is also muddied by the extensive repetition making it hard to follow the actual sequence. | 2 / 3 |
Progressive Disclosure | References external files (templates/viewer.html, templates/generator_template.js) which is good progressive disclosure, but the SKILL.md itself is monolithic with massive inline content that could be split out. The philosophy examples, HTML structure details, and sidebar specifications could all be in separate reference files. The main file tries to contain everything. | 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.
- Repository
- duclm1x1/Dive-Ai
- Commit
20ba150
- Reviewed
Table of Contents
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