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visual-validation

Autonomous screenshot verification — captures, compares, and AI-evaluates UI changes for visual regressions

55

Quality

69%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./skills/visual-validation/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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 is actionable and reasonably well-structured with a validation-gated workflow, but suffers from redundant capture-command repetition and motivational padding. The comparison/regression-handling step is the weakest part of the flow.

Suggestions

Collapse the repeated peekaboo capture command into a single canonical example and reference it from the other sections to reduce redundancy.

Replace the vague baseline-comparison step ("ls -la ... review pairs") with a concrete diff command and add a feedback loop describing what to do when REGRESSION_DETECTED fires.

Trim the Philosophy section's motivational framing ("the machine verifies what the machine built") to tighten token efficiency.

DimensionReasoningScore

Conciseness

The Philosophy section is motivational padding and the same peekaboo capture command recurs across four sections (Autonomous Flow, Quick Commands, Autonomous Verification Flow, Maggy Dashboard Verification), so it is mostly efficient but noticeably redundant.

3 / 5

Actionability

Concrete executable commands throughout (peekaboo image, lsof|xargs kill, curl health check, gemini-api --flash) give mostly copy-paste-ready guidance with only minor gaps.

4 / 5

Workflow Clarity

The 7-step flow has a health-check validation checkpoint guarding the destructive kill, but the baseline-comparison step is vague and there is no feedback loop for when a regression is detected.

4 / 5

Progressive Disclosure

Single-file content (no bundle files exist) is organized into clear, well-labeled sections; slightly over 50 lines so it does not qualify for the simple-skill 5, but structure is clean.

4 / 5

Total

15

/

20

Passed

Description

58%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.

The description is specific and occupies a clear niche, but omits an explicit 'when to use' trigger inside the description field itself, capping completeness. Trigger-term coverage is decent but lacks common synonyms.

Suggestions

Append an explicit 'Use when...' clause to the description (e.g. "Use when a UI or static-asset change needs visual verification before shipping") so completeness is not capped at 3.

Add natural trigger synonyms users would actually say, such as "visual diff", "before/after screenshot", or "UI regression", to lift trigger-term quality.

Mention the baseline-comparison mechanism in the description to round out specificity toward comprehensive coverage.

DimensionReasoningScore

Specificity

"captures, compares, and AI-evaluates UI changes for visual regressions" names several concrete actions, but stops short of the comprehensive coverage (e.g. baseline diffing, threshold tuning) needed for a 5.

4 / 5

Completeness

The description gives a clear "what" but no "Use when..." trigger clause (the trigger lives in a separate when-to-use field), so per the rubric completeness is capped at 3.

3 / 5

Trigger Term Quality

Natural terms like "screenshot", "UI changes", and "visual regressions" appear, but common synonyms users would say ("visual diff", "before/after", "UI regression") are missing.

3 / 5

Distinctiveness Conflict Risk

"Autonomous screenshot verification" for visual regressions is a distinct niche with minimal overlap risk against other skills, fitting the mostly-distinct anchor.

4 / 5

Total

14

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

alinaqi/maggy

Path

skills/visual-validation/SKILL.md

Reviewed

Table of Contents

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