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Magnus HedemarkandGitHub
b57fe513e8
Merge dedicated AEO skill with implementation references, templates, scripts, evals, and SEO routing.
46 lines
2.6 KiB
Markdown
46 lines
2.6 KiB
Markdown
# AEO
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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.
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## Why Install This Skill
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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.
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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.
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## What You Get
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| Path | Purpose |
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|---|---|
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| `SKILL.md` | AEO routing, implementation loop, decision rules, and completion gate |
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| `references/` | Evidence boundaries, implementation, content architecture, structured data, discovery, platform guidance, and measurement |
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| `templates/` | Implementation plan, question cluster, citation log, `llms.txt`, and crawler policy templates |
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| `scripts/aeo_audit.py` | Read-only structural audit of a local HTML file or URL |
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| `scripts/build_prompt_matrix.py` | Deterministic prompt-set generation from topics and questions |
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| `scripts/test_aeo_scripts.py` | Offline regression tests for the bundled scripts |
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| `evals/evals.json` | Output-quality evaluation cases |
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## Quick Start
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```bash
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python3 scripts/aeo_audit.py https://example.com/article --json
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python3 scripts/build_prompt_matrix.py topics.json --output prompts.json
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```
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Both commands are read-only and use only Python's standard library. They do not call an LLM or modify the target site.
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## Triggers
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- Implement Answer Engine Optimization, AEO, GEO, LLMO, or AI-search visibility
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- Make a page more likely to be understood, retrieved, cited, or correctly summarized by answer engines
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- Build question clusters, answer-first content, evidence blocks, or citation measurement
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- Implement or assess `llms.txt`, AI crawler controls, Markdown delivery, schema parity, or freshness signals
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- Design a reproducible prompt set or AI-answer citation experiment
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## Requirements
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- Python 3.9+ for bundled scripts
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- Network access only when auditing a URL; local HTML files work offline
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- No API keys required
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- Provider dashboards, CMS credentials, and search-console access are optional and must be handled by their own operational skills
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