AC geo-first-seo
Use this skill when the user wants to make content more likely to be cited or surfaced by AI answer engines (ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot) — i.e. Generative Engine Optimization / GEO / "AI SEO". Covers an end-to-end workflow: GEO strategy and query research, creating new GEO-optimized content or auditing/rewriting an existing page or article, technical markup (schema.org JSON-LD, llms.txt, FAQ/heading structure), and a GEO scorecard. Not for traditional keyword-ranking SEO audits, paid ads, or link-building campaigns.
e. Generative Engine Optimization / GEO / "AI SEO". Covers an end-to-end workflow: GEO strategy and query research, creating new GEO-optimized content or…
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- 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: 6. 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 59/100
- 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. 7 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 25 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1947 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +5Description has no quoted example phrases that should trigger the skill
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 552: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 25 items
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.