Diagnose a brand, website, or page for evidence-backed GEO gaps and opportunities from user-supplied URLs, HTML, or evidence. Use for brand diagnosis, website or page audits, GEO gap analysis, and 品牌诊断、网站诊断、页面诊断. Excludes live AI-platform recall, ranking, and citation-share measurement.
Resources
6Install
npx skillscat add yaojingang/geohub/geo-diagnose Install via the SkillsCat registry.
We need to produce a 2-3 sentence plain-text summary, objective, factual, no marketing, no superlatives, no calls to action, natural prose, no bullet points, no headings, no markdown. At most 60 words. Must be only the summary text, no quotes. We need to summarize the skill: Diagnose a brand, website, or page for evidence-backed GEO gaps and opportunities from user-supplied URLs, HTML, or evidence. Use for brand diagnosis, website or page audits, GEO gap analysis, and Chinese terms. Excludes live AI-platform recall, ranking, citation-share measurement.
GEO Diagnose
Workflow
- Read
references/diagnosis-method.md; readreferences/audit-catalog.mdfor non-legacy audit execution. - Prepare the diagnosis brief contract.
- Run
python3 scripts/run_diagnose.py --input <brief.json> --output <runs-root> --execution-mode <legacy|deterministic|research|provider>. Legacy remains the compatibility default. - Inspect
quality-report.json,run-lineage.json,source_status, audit components, and limitations before using findings. - Deliver the complete Artifact Bus run directory.
Output contract
Return <runs-root>/<run-id>/ containing the normalized input and replayable HTML snapshots under input/sources/, structured diagnosis, deterministic Markdown report, evidence-linked remediation query map, opportunity map, quality report, run lineage, and run manifest. Non-legacy diagnosis adds versioned audit results, reconstructable score components, execution status, and a semantic digest to diagnosis.json.
Boundaries
Fetch only explicit public HTTP(S) canonical URLs without query strings. Accept remote HTML/XHTML only and keep unavailable or unsupported sources as source_gap. Every observed, provided, or inferred finding carries a content-derived evidence ID. Provider audit mode has no packaged adapter and records a degraded deterministic fallback. Never claim live AI-platform recall, ranking, or citation share.