yaojingang

geo-diagnose

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.

yaojingang 136 23 Updated 3w ago

Resources

6
GitHub

Install

npx skillscat add yaojingang/geohub/geo-diagnose

Install via the SkillsCat registry.

About this skill

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.

SKILL.md

GEO Diagnose

Workflow

  1. Read references/diagnosis-method.md; read references/audit-catalog.md for non-legacy audit execution.
  2. Prepare the diagnosis brief contract.
  3. Run python3 scripts/run_diagnose.py --input <brief.json> --output <runs-root> --execution-mode <legacy|deterministic|research|provider>. Legacy remains the compatibility default.
  4. Inspect quality-report.json, run-lineage.json, source_status, audit components, and limitations before using findings.
  5. 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.