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.

1.80x

Quality

67%

Does it follow best practices?

Impact

54%

1.80x

Average score across 10 eval scenarios

Securityby

Advisory

Suggest reviewing before use

Fix and improve this skill with Tessl

tessl review fix ./docs/v19.7/configuration/agent/skills_external/antigravity-awesome-skills-main/skills/algorithmic-art/SKILL.md

Quality

Content

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 excessively verbose, repeating key instructions (use the template, emphasize craftsmanship, philosophy length) multiple times throughout. While it provides a creative framework for generative art, the actual technical guidance is surprisingly thin — mostly abstract direction rather than concrete, executable patterns. The skill would benefit enormously from being cut to ~40% of its current length and replacing philosophical repetition with more concrete implementation examples.

Suggestions

Cut content by at least 50%: remove repeated instructions about using the template (mentioned 6+ times), craftsmanship emphasis (mentioned 4+ times), and philosophy length (mentioned 3+ times). State each instruction once.

Replace the 5 condensed philosophy examples with 1-2 complete examples showing the full pipeline from user request → philosophy → actual working code, so Claude has a concrete end-to-end reference.

Add validation checkpoints: after generating the HTML artifact, include steps to verify seed reproducibility works, all controls are functional, and the p5.js sketch renders correctly.

Move the philosophy examples and detailed HTML structure specifications into separate bundle files (e.g., examples/philosophies.md and templates/sidebar-spec.md) to reduce the main SKILL.md to an actionable overview.

Dimension	Reasoning	Score
Conciseness	Extremely verbose at ~400+ lines. Repeats the same concepts multiple times (e.g., 'meticulously crafted' emphasis repeated 4+ times, 'use the template' repeated 6+ times, philosophy length guidance repeated 3 times). Explains creative processes Claude already understands, and includes extensive philosophy examples that bloat the content significantly.	1 / 3
Actionability	Provides some concrete code snippets (seeded randomness, canvas setup, HTML structure) but much of the guidance is abstract and philosophical rather than executable. The code examples are incomplete fragments rather than copy-paste ready implementations. The actual algorithm creation is left entirely vague ('let the philosophy guide the implementation').	2 / 3
Workflow Clarity	The two-step process (philosophy → implementation) is clearly stated, and there's a numbered creative process at the end. However, there are no validation checkpoints, no error recovery steps, and the workflow is muddied by extensive repetition and interleaving of concerns. Step 0 (read template) is emphasized but there's no verification that the output works correctly.	2 / 3
Progressive Disclosure	References templates/viewer.html and templates/generator_template.js appropriately, but no bundle files were provided to verify these exist. The SKILL.md itself is monolithic — the philosophy examples, implementation details, and UI specifications could be split into separate reference files. The content that should be in the template files is partially duplicated inline.	2 / 3
	Total	7 / 12 Passed

Description

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 behavioral constraint. 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 trigger scenarios). Also includes a behavioral constraint about avoiding copyright violations.	3 / 3
Trigger Term Quality	Includes strong natural trigger terms users would actually say: 'generative art', 'algorithmic art', 'flow fields', 'particle systems', 'art using code', '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

Validation

100%

Warnings & errors only

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: 5 months ago

Table of Contents

Discovery Implementation Validation

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.