Magnus Hedemarkandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
a9e93c023a
Convert the prose script list into an Available Scripts table covering aeo_audit.py, build_prompt_matrix.py, and test_aeo_scripts.py with copy-pasteable invocations and run-when guidance; add Prerequisites and Limitations derived from the skill's compatibility notes. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
AEO
A focused implementation methodology for Answer Engine Optimization: making useful, attributable answers discoverable and reusable by AI search systems without relying on folklore or guaranteed “AI ranking” hacks.
Why Install This Skill
AEO advice is full of confident claims that collapse different systems, measurements, and goals into one vague promise. This skill gives your agent a disciplined way to research the actual target surface, map questions to owned answers, implement useful content and machine-readable signals, and measure citations with reproducible evidence.
It is intentionally narrower than SEO. Use it for answer architecture, question clusters, entities, citations, provider crawler controls, optional agent-readable files, and AI-answer experiments. Hand broad search audits and CMS-specific changes to the existing SEO and platform skills.
What You Get
| Path | Purpose |
|---|---|
SKILL.md |
AEO routing, implementation loop, decision rules, and completion gate |
references/ |
Evidence boundaries, implementation, content architecture, structured data, discovery, platform guidance, and measurement |
templates/ |
Implementation plan, question cluster, citation log, llms.txt, and crawler policy templates |
scripts/aeo_audit.py |
Read-only structural audit of a local HTML file or URL |
scripts/build_prompt_matrix.py |
Deterministic prompt-set generation from topics and questions |
scripts/test_aeo_scripts.py |
Offline regression tests for the bundled scripts |
evals/evals.json |
Output-quality evaluation cases |
Quick Start
python3 scripts/aeo_audit.py https://example.com/article --json
python3 scripts/build_prompt_matrix.py topics.json --output prompts.json
Both commands are read-only and use only Python's standard library. They do not call an LLM or modify the target site.
Triggers
- Implement Answer Engine Optimization, AEO, GEO, LLMO, or AI-search visibility
- Make a page more likely to be understood, retrieved, cited, or correctly summarized by answer engines
- Build question clusters, answer-first content, evidence blocks, or citation measurement
- Implement or assess
llms.txt, AI crawler controls, Markdown delivery, schema parity, or freshness signals - Design a reproducible prompt set or AI-answer citation experiment
Requirements
- Python 3.9+ for bundled scripts
- Network access only when auditing a URL; local HTML files work offline
- No API keys required
- Provider dashboards, CMS credentials, and search-console access are optional and must be handled by their own operational skills