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aeo-optimization

AI Engine Optimization - semantic triples, page templates, content clusters for AI citations

50

Quality

63%

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tessl review fix ./skills/aeo-optimization/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

57%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 delivers strong, concrete, copy-paste-ready guidance — templates, schema markup, and worked examples that make it genuinely usable — but it is a 556-line monolith that repeats its own rules across checklists and a quick-reference section and buries five full templates inline instead of splitting them into reference files. It also lacks an explicit end-to-end workflow showing how to apply the patterns to a single page. Restructuring would lift conciseness and progressive disclosure together.

Suggestions

Move the five page templates (and the schema JSON-LD blocks) into separate files under references/ (e.g., references/templates.md, references/schema.md) and keep a short overview with one-line pointers, cutting the body by more than half.

Add an explicit numbered workflow — pick template → draft sections using Feature → How → Outcome → insert triples → run per-page checklist → add schema → verify with the measurement queries — so the sequence is explicit rather than implied by document order.

Deduplicate the triple-restatement of rules across 'AEO Writing Checklist', 'Page Minimums', and 'Quick Reference' into a single checklist, and drop the decorative ASCII art and dated market stats or move them to a clearly-labeled context section.

DimensionReasoningScore

Conciseness

The 556-line body restates the same rules three times (per-page checklists, 'Page Minimums', and 'Quick Reference'), includes decorative ASCII art panels, and embeds time-sensitive stats ('47% of Google queries', '$886M (2024) → $7.3B (2031)') outside any deprecated section — mostly efficient but with noticeable tightening opportunities, sitting between anchors 2 and 3.

3 / 5

Actionability

Five copy-paste-ready page templates, complete executable JSON-LD schema markup, concrete good/bad triple examples, and a worked paragraph example make the core guidance highly actionable; the gap is the measurement section, which lists metric names with vague tracking directions ('Manual checks in ChatGPT, Claude, Perplexity') and no example queries or GA4 setup steps, matching anchor 4 rather than 5.

4 / 5

Workflow Clarity

There is no explicit step-by-step sequence for applying the skill to a page (e.g., choose template → draft with Feature → How → Outcome → run checklists → add schema → validate); the underlying flow is implicit in document order, and while the checklists function as checkpoints, the sequence itself is missing, matching anchor 3.

3 / 5

Progressive Disclosure

The body is well-sectioned with clear headers, but it is entirely monolithic: five ~50-line page templates, the schema implementation code, and four checklist tiers that clearly belong in separate reference files are all inlined, and no bundle files (references/, scripts/, assets/) or external file pointers exist, matching the 'content that should be separate is inline' anchor.

3 / 5

Total

13

/

20

Passed

Description

53%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 clearly identifies the domain and its core artifacts but reads as a noun phrase rather than a capability statement, lacks action verbs, and omits any 'Use when...' trigger clause within the description field itself. Keyword coverage misses common user phrasings like 'AEO', 'AI search', or 'ChatGPT citations'. It is reasonably distinct from other skills but sits in the middle of the rubric on most dimensions.

Suggestions

Add an explicit trigger clause to the description, e.g. 'Use when optimizing content for AI search engines, AEO/GEO, or when the user wants their brand cited by ChatGPT, Claude, Perplexity, or Google AI Overviews.'

Lead with action verbs describing capabilities (e.g. 'Rewrites and structures content using semantic triples, applies page templates, and builds content clusters to earn AI citations') instead of a bare noun list.

Include natural synonyms users would actually say — 'AEO', 'generative engine optimization', 'AI search visibility', 'ChatGPT/Perplexity citations' — to improve trigger-term coverage.

DimensionReasoningScore

Specificity

Names the domain ('AI Engine Optimization') and three concrete deliverables ('semantic triples, page templates, content clusters for AI citations'), but is a noun list with no action verbs describing what the skill actually does, matching the 'names domain and concrete actions but not comprehensive' anchor rather than the 'several specific actions' level.

3 / 5

Completeness

The 'what' is clearly present, but the description field itself contains no 'Use when...' clause or equivalent trigger guidance (trigger guidance exists only in a separate when-to-use frontmatter field), which caps completeness at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

Includes relevant keywords like 'AI citations' and 'AI Engine Optimization' but misses natural variations users would say such as 'AEO', 'GEO', 'AI search', 'AI Overviews', or 'get cited by ChatGPT/Perplexity', fitting the 'some relevant keywords but missing common variations' anchor.

3 / 5

Distinctiveness Conflict Risk

The niche is fairly distinct — 'semantic triples', 'content clusters', and 'AI citations' are specific to AEO — with only minor overlap risk against general SEO/content-marketing skills, matching the 'mostly distinct; minor overlap risk' anchor.

4 / 5

Total

13

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (556 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository

alinaqi/maggy

Path

skills/aeo-optimization/SKILL.md

Reviewed

Table of Contents

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