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geo-platform-optimizer

Platform-specific AI search optimization — audit and optimize for Google AI Overviews, ChatGPT, Perplexity, Gemini, and Bing Copilot individually

62

Quality

75%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/geo-platform-optimizer/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

The content is highly actionable with concrete checklists, scoring rubrics, and a report template, and the workflow is clearly sequenced; its weaknesses are length/redundancy and a monolithic single-file structure with no progressive disclosure into reference files.

Suggestions

Trim the 'Core Insight' preamble and the 'Cross-Platform Summary' table, which restate points already in each platform's checklist, to tighten conciseness.

Split each platform's 'How X selects sources' + checklist detail into one-level-deep reference files (e.g. references/google-aio.md) and keep SKILL.md as an overview with signaled links.

Consider adding a brief validation step in the workflow (e.g. re-check that per-platform scores sum to 100 before emitting the report) to formalize the audit output.

DimensionReasoningScore

Conciseness

The body is information-dense and avoids explaining concepts Claude already knows, but at ~275 lines it carries redundancy — the 'Core Insight' stat preamble and the 'Cross-Platform Summary' table restate platform points already covered in each checklist.

2 / 3

Actionability

Each platform has a specific checklist (e.g. 'Submit a key file at /.well-known/indexnow-key.txt and ping the IndexNow API'), exact 0-100 scoring rubrics with point allocations, and a copy-paste output template — fully concrete and actionable.

3 / 3

Workflow Clarity

'How to Use This Skill' gives a clear four-step sequence (collect URL → run each checklist → score 0-100 → generate report) with a structured output format; the task is a read-only audit so no destructive-operation validation checkpoint is required.

3 / 3

Progressive Disclosure

Sections are well-organized within a single file, but there are no bundle files and all five platform deep-dives live inline in one 275-line SKILL.md rather than being split into one-level-deep reference files.

2 / 3

Total

10

/

12

Passed

Description

72%

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 distinctive with strong natural trigger terms via the named platforms, but it lacks an explicit 'when to use' clause and only offers two broad actions, capping completeness and specificity at 2.

Suggestions

Add a 'Use when...' clause naming triggering situations, e.g. 'Use when the user wants to be cited in AI search engines or asks about GEO/AEO across ChatGPT, Google AI Overviews, Perplexity, Gemini, or Bing Copilot.'

Expand the two actions into more concrete verbs (audit, score, benchmark, generate an optimization report) to lift specificity toward level 3.

Include common shorthand trigger terms users say ('GEO', 'AEO', 'AI search', 'LLM search') alongside the platform names.

DimensionReasoningScore

Specificity

It names the domain ('AI search optimization') and enumerates five concrete platforms (Google AI Overviews, ChatGPT, Perplexity, Gemini, Bing Copilot), but only offers two actions ('audit and optimize') rather than the multiple distinct actions a level-3 anchor calls for.

2 / 3

Completeness

It clearly answers 'what' (audit and optimize per platform) but provides no 'Use when...' or equivalent explicit trigger guidance, which caps completeness at 2 per the rubric guideline.

2 / 3

Trigger Term Quality

It lists the exact platform names users naturally invoke (ChatGPT, Perplexity, Gemini, Bing Copilot, Google AI Overviews), giving good coverage of natural trigger terms rather than jargon.

3 / 3

Distinctiveness Conflict Risk

The platform-specific GEO niche and named platforms make it clearly distinguishable from other skills and unlikely to trigger for the wrong skill.

3 / 3

Total

10

/

12

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.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository
zubair-trabzada/geo-seo-claude
Reviewed

Table of Contents

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