CtrlK
BlogDocsLog inGet started
Tessl Logo

geo-fundamentals

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

48

Quality

51%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/geo-fundamentals/SKILL.md

The canonical home for this skill is geo-fundamentals in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

55%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 a lean, well-structured reference of compact tables plus one bundled audit script, but it functions as a knowledge sheet rather than executable guidance: it lacks implementation templates, a sequenced workflow, and any validation steps.

Suggestions

Add concrete, copy-paste-ready examples for the checklist items (e.g., a sample Article/FAQPage JSON-LD block and a question-based title template) to lift actionability.

Define a short sequenced workflow with a validation checkpoint, e.g. run geo_checker.py -> review citation-readiness gaps -> apply fixes -> re-run, rather than leaving the audit as a bare command.

Move the longer reference tables (RAG factor weights, crawler list) into a references/ file linked from SKILL.md so the overview stays scannable.

DimensionReasoningScore

Conciseness

The body is almost entirely compact reference tables with little prose padding, and it largely avoids re-explaining concepts Claude already knows; only minor trims are needed (the "What is GEO?" definition and the closing "Remember" line).

4 / 5

Actionability

There is one concrete executable command ("python scripts/geo_checker.py <project_path>") and specific checklist items, but most guidance is high-level advice without templates or code (e.g., "Article schema with dates" with no markup example), leaving key execution details missing.

3 / 5

Workflow Clarity

Sections 1-9 provide a topical order (what -> landscape -> factors -> content -> checklist -> measurement) but no sequenced workflow, and validation/checkpoints are entirely absent even around the audit script.

2 / 5

Progressive Disclosure

Content is well-organized into clearly headed sections, and the one bundled file (scripts/geo_checker.py, confirmed present) is clearly signaled with its command; most reference material is appropriately inline, with only minor opportunity to split detailed tables out.

4 / 5

Total

13

/

20

Passed

Description

48%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 names a distinct, on-trend niche but is thin: it states a domain and platform list without concrete actions or any explicit "when to use" trigger guidance. It reads as a label rather than a trigger-ready capability statement.

Suggestions

Add 1-2 concrete actions, e.g. "Audits content for AI-citation readiness and recommends entity, schema, and freshness improvements".

Append an explicit trigger clause, e.g. "Use when the user wants content cited by ChatGPT, Claude, Perplexity, or Gemini, or asks about AI/LLM search visibility."

Include natural synonyms users actually say ("AI citations", "AI search visibility", "LLM search") to broaden trigger coverage.

DimensionReasoningScore

Specificity

The description names the domain ("Generative Engine Optimization") and the platforms ("ChatGPT, Claude, Perplexity"), but the only action named is the generic "Optimization" with no concrete actions such as audit, optimize, or measure.

2 / 5

Completeness

It conveys a clear-ish "what" (GEO for AI search engines) but provides no "Use when..." or equivalent trigger guidance, so per the rubric completeness is capped at 3.

3 / 5

Trigger Term Quality

It includes relevant natural keywords ("AI search engines" and the platform names ChatGPT, Claude, Perplexity), but misses common variations users would say such as "AI citations", "AI visibility", "LLM search", or "AI answers".

3 / 5

Distinctiveness Conflict Risk

The AI-search-engine niche is distinct from traditional SEO and the named platforms narrow it, leaving only minor overlap risk with general content-optimization or SEO skills.

4 / 5

Total

12

/

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.

Validation15 / 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
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.