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.

Quality

67%

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Passed

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tessl review fix ./.agent/skills/algorithmic-art/SKILL.md

Quality

Content

35%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This SKILL.md functions primarily as a table of contents pointing to 11 sub-skill files, with almost no actionable content in the main file itself. The two-step workflow is stated but not elaborated, and there are no code examples, concrete commands, or specific guidance. The skill would benefit greatly from including at minimum a quick-start example and brief descriptions of what each sub-skill covers.

Suggestions

Add a concrete quick-start example showing a minimal p5.js generative art piece with seeded randomness, so the main file has standalone actionable value.

Add 1-2 sentence descriptions next to each sub-skill link explaining what it covers and when to reference it, rather than bare titles.

Include at least one complete executable code example (HTML + JS) demonstrating the expected output format.

Clarify the workflow by specifying which sub-skills correspond to which step, and add validation checkpoints (e.g., 'verify the philosophy .md meets criteria X before proceeding to code generation').

Dimension	Reasoning	Score
Conciseness	The content is relatively brief but includes some unnecessary framing language ('Algorithmic philosophies are computational aesthetic movements') and bullet points that describe concepts rather than instruct. The emoji usage and dramatic formatting ('⚠️ STEP 0: READ THE TEMPLATE FIRST ⚠️') add noise.	2 / 3
Actionability	The SKILL.md contains no executable code, no concrete commands, and no specific examples. It describes what to create at a high level ('create an ALGORITHMIC PHILOSOPHY') but delegates all actual guidance to 11 sub-skill files, leaving the main file with essentially zero actionable content.	1 / 3
Workflow Clarity	There is a two-step process mentioned (philosophy creation then p5.js expression), but the steps lack any detail, validation checkpoints, or error recovery. The 11 sub-skills are numbered but their sequencing relationship is unclear—some seem like references rather than sequential steps (e.g., 'PHILOSOPHY EXAMPLES' vs 'TECHNICAL REQUIREMENTS').	2 / 3
Progressive Disclosure	The skill does reference 11 sub-skill files which suggests progressive disclosure, but the references are poorly signaled—they have titles but no descriptions of what each contains or when to consult them. With no bundle files provided to verify these references exist, and 11 separate files being an unusually high number, the navigation burden is significant. The main file provides almost no standalone value.	2 / 3
	Total	7 / 12 Passed

Description

100%Scale 1-3

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 algorithmic/generative art using p5.js. It provides specific capabilities, explicit trigger terms via a 'Use when' clause, and distinguishes itself well from general coding or art skills. The additional note about avoiding copyright violations adds useful behavioral guidance.

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 ('Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems'). Includes an explicit 'Use when' clause with specific triggers.	3 / 3
Trigger Term Quality	Includes strong natural trigger terms users would actually say: 'generative art', 'algorithmic art', 'art using code', '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 niche combining p5.js, generative/algorithmic art, seeded randomness, and specific techniques like flow fields and particle systems. Unlikely to conflict with general coding or general art skills due to the specific domain focus.	3 / 3
	Total	12 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: Dokhacgiakhoa/antigravity-ide
Path: .agent/skills/algorithmic-art/SKILL.md
Commit: c4a059b

Reviewed: 3 days ago

Table of Contents

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