AC ai-search-optimization
Use to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill. Run when the user says "GEO," "get cited by ChatGPT/Perplexity/Google AI," "ChatGPT SEO," "LLM SEO / LLMO," "AI Overviews," "answer engine optimization (AEO)," "will AI recommend my brand," or wants to show up in AI-generated answers, not just the feed or Google links. Reads brand-profile and audience first. AI engines retrieve + fan-out and cite community/social sources heavily (Reddit, YouTube, Wikipedia); platforms disagree; earned media beats product pages; extractable, fresh content drives citation. Covers the four GEO levers (retrievable, earned mentions, extractable content, entity clarity), authentic social plays, and the manual prompt-audit method. Refuses astroturfing; never fabricates "share of voice." Sibling of social-seo (platform + Google search). Judges via the audit + GEO tools + AI referral traffic.
Use to get a brand and its content CITED and RECOMMENDED by AI answer engines — the GEO (Generative Engine Optimization) / AI-search-visibility skill.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 62/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 4 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 25 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1749 tokens
- low 12 top-level sections: this looks like several domains in one skill
- low No test case covers injection arriving through data
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 979: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +4Structure: 13 headings
- +3Step-by-step instructions: 25 items
- +4Reference files are cited in the instructions (4 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.