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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.

55

1.80x
Quality

66%

Does it follow best practices?

Impact

54%

1.80x

Average score across 10 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/anthropic-algorithmic-art/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

48%Weight 40%Scale 1-5

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

The body establishes a clear two-phase workflow with some genuinely concrete code and HTML snippets, but it is significantly padded — mandated repetition, redundant template sections, and five full example philosophies. More critically, the entire implementation hinges on template files that are not present in the bundle, and large chunks of reference material are inlined instead of split out.

Suggestions

Include templates/viewer.html and templates/generator_template.js in the bundle (or inline the essential fixed structure once), since the workflow's required starting point currently points to nonexistent files.

Consolidate the template instructions repeated across STEP 0, "CRITICAL: WHAT'S FIXED VS VARIABLE", and RESOURCES into a single section, and remove the instruction to repeat craftsmanship phrases multiple times — it adds tokens without adding information.

Move the five philosophy examples and the full HTML artifact skeleton into a one-level-deep reference file, keeping SKILL.md as a lean overview with clearly signaled pointers.

DimensionReasoningScore

Conciseness

Noticeably verbose across ~400 lines: it mandates repetition ("Emphasize craftsmanship REPEATEDLY ... stress multiple times"), includes five full-paragraph philosophy examples, repeats the same template fixed/variable rules in three separate sections (STEP 0, INTERACTIVE ARTIFACT CREATION, RESOURCES), and pads with rhetoric ("Think like a jazz musician quoting another song through algorithmic harmony"). Fits anchor 2; not 1 because it does not lecture at length on concepts Claude already knows, and not 3 because the redundancy is substantial rather than incidental.

2 / 5

Actionability

There is concrete guidance — "Read `templates/viewer.html` using the Read tool", a literal sidebar control HTML snippet, the p5.js CDN URL, and seeded-randomness code — but the "REQUIRED STARTING POINT" template file does not exist in the bundle, and the p5.js blocks are skeletons ("// Your generative algorithm"). The missing central dependency and skeletal code leave key details missing, matching anchor 3 rather than 4's "minor gaps".

3 / 5

Workflow Clarity

The two-phase sequence is stated up front ("This happens in two steps: 1. Algorithmic Philosophy Creation ... 2. Express by creating p5.js generative art") and followed by ordered sections (STEP 0 read-the-template, deduce conceptual seed, implement, output) with a "works immediately in claude.ai or any browser" check. Falls short of anchor 5 because there is no explicit verify/recover loop and the duplicated template instructions slightly muddy the sequence; clearly above anchor 3's implicit-checkpoint level.

4 / 5

Progressive Disclosure

References to templates/viewer.html and templates/generator_template.js are clearly signaled and one level deep, but neither file exists in the bundle (broken references), and content that belongs in them — the full inline HTML skeleton, the five philosophy examples, and the repeated fixed/variable lists — is inlined in SKILL.md. This matches anchor 3's "content that should be separate is inline"; not 4 because broken references and heavy inlining exceed "minor organization gaps".

3 / 5

Total

12

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: third-person, concise, with an explicit "Use this when" trigger clause covering natural terms. The what/when split is concrete and the niche is distinctive, with only minor gaps in capability coverage and slight overlap risk from simulation-adjacent trigger terms.

DimensionReasoningScore

Specificity

Names several concrete capabilities — "Creating algorithmic art using p5.js", "seeded randomness", "interactive parameter exploration" — but coverage has gaps: the philosophy/manifesto step and HTML artifact outputs from the body are unmentioned. Fits anchor 4 rather than 3 (more than 1-2 actions) or 5 (not comprehensive).

4 / 5

Completeness

Explicitly 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"). The trigger guidance is explicit with concrete phrases, matching the anchor-5 example structure.

5 / 5

Trigger Term Quality

"creating art using code, generative art, algorithmic art, flow fields, or particle systems" gives good natural-term coverage users would actually say. Not 5 because common synonyms like "creative coding" or "p5 sketch" are missing; not 3 since coverage goes well beyond "some relevant keywords".

4 / 5

Distinctiveness Conflict Risk

A clear niche (generative/algorithmic art in p5.js) with distinct triggers, but "flow fields" and "particle systems" could also match physics-simulation or data-visualization requests, creating minor overlap risk. Fits anchor 4 better than 5's "minimal conflict risk".

4 / 5

Total

17

/

20

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
boisenoise/skills-collections
Reviewed

Table of Contents

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