一键在 Manus 中运行任何 Skill

semantic-site-auditor

星标5

分支0

更新时间2026年7月3日 21:51

Audit an existing site against its topical map — coverage gaps, keyword cannibalization, entity drift, orphan pages, and per-page micro-semantic issues. Use whenever the user asks to audit a site, find content gaps, check for cannibalization, asks "why aren't we ranking", wants to know what's missing from their niche coverage, or wants a pre-sales content audit of any domain. Produces a prioritised audit report with provenance on every finding. Triggers on audit/gap/cannibalization intent broadly.

安装

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

在 Manus 中运行

来源

siddiqss

siddiqss/semantic-seo-suite

打开 GitHub 仓库查看创作者相关仓库

下载

在 Manus 中运行

semantic-site-auditor

Turn a live site + its topical map into a prioritised, evidence-backed fix list. Every finding carries provenance (measured from crawl, derived from embeddings) — no invented scores. This is also the strongest pre-sales artifact for services work: run it on a prospect's domain before a call.

Read first: ../../framework/topical-map-theory.md (gap/section logic), ../../framework/internal-linking-rules.md (orphans), ../../framework/eav-modeling.md (drift = claimed vs perceived identity).

Preconditions

brands/<slug>/config.yaml (tier).
A topical-map.json to audit against. If none exists, run topical-map-builder first (you can't measure coverage without a target map).
entity-profile.json (for the claimed-identity centroid used by drift).

Workflow

Crawl + extract the site into brands/<slug>/data/crawl/:
```
python ../../scripts/crawl_sitemap.py --domain <domain> --max-pages 500 --out /tmp/urls.json
python ../../scripts/extract_page_content.py --urls /tmp/urls.json --out-dir brands/<slug>/data/crawl
```
Robustness: crawl_sitemap.py falls back to a same-domain BFS when there's no sitemap, respects robots.txt, and caps pages/depth. For JS-rendered sites, extraction may be thin — note that in the report rather than treating missing content as a gap.
Run the analysis engine:
```
python ../../scripts/audit_site.py \
  --map brands/<slug>/topical-map.json --crawl-dir brands/<slug>/data/crawl \
  --entity-profile brands/<slug>/entity-profile.json \
  --locked brands/<slug>/locked-facts.json --brand "<Brand>" \
  --out brands/<slug>/audits/<date>-full.md
```
It matches each page to its nearest map node (embedding cosine) and reports:
- Coverage gaps — nodes with no matching page (derived).
- Cannibalization — page pairs with high similarity + same intent, and any node hit by multiple pages (derived).
- Entity drift — pages farthest from the core-section centroid, i.e. content pulling the site away from its claimed identity (derived). At T0 (no embeddings), do this qualitatively and label it asserted — never emit a fake distance.
- Orphans — pages with no incoming internal links (measured from the crawl link graph).
- Micro-audit — per-page lint (naked stats, fluff, unanswered question headings) reusing the draft rules.
Review + prioritise. The report ends with a prioritised action list: create (gap), consolidate/redirect (cannibalization), rewrite/relink or prune (drift), relink (orphan). Sanity-check each finding — with the offline hash-fallback embeddings, similarities are coarse; re-run with a model backend before making irreversible calls (redirects/prunes).
Feed back into the map. Apply status_updates from the audit JSON (matched nodes → published with their URL); mark thin/drifting matched nodes needs-update; add the confirmed gaps to calendar.md as new priorities.
Render the heatmap (../../scripts/map_heatmap.py) after status updates so coverage is visible at a glance.

Definition of done

Report produced with all five finding types, each provenance-tagged.
At least one finding is verifiable by hand (a true gap or a true cannibalization pair).
Map statuses updated; gaps flowed into the calendar.
No fabricated scores anywhere (drift/cannibalization are derived or clearly asserted).

Grounding ladder

T0: crawl + extract still work (they're just HTTP); matching/cannibalization/drift are LLM-qualitative and labeled asserted. Orphans + micro-audit are measured.
T1: embedding-based matching/cannibalization/drift (derived) — the real version.
T1+GSC: confirm cannibalization with pages sharing top queries in Search Console (the strongest, measured signal) — see seo-performance-tracker.

同仓库更多 Skills

同仓库

answer-engine-optimizer

siddiqss/semantic-seo-suite

Optimize a brand's mapped content to get cited by AI answer engines — Google AI Overviews, ChatGPT, Perplexity, Gemini. Scores drafts for citation-readiness with aeo_score.py, produces a per-node hardening checklist, and spot-checks live AI answers for whether the brand (vs competitors) is cited. Use whenever the user mentions AEO, GEO, LLM SEO, "getting cited by ChatGPT/Perplexity", AI Overviews, answer engines, AI search visibility, or asks why an AI assistant recommends competitors and not them. The GEO half of seo-performance-tracker. Never invents a visibility score. Triggers on AI-visibility / answer-engine intent broadly.

2026-07-035

content-brief-generator

siddiqss/semantic-seo-suite

Generate entity-aware, Koray-style content briefs from a topical-map node or any target query — a semantically ordered heading skeleton with entity/attribute tags, internal-link targets, snippet target, word budgets, locked-facts references, and a do-not-fabricate list. Use whenever the user asks for a content brief, an article outline, writer instructions, "brief for X", or wants to start writing an article that exists in the topical map. Runs SERP recon first. Triggers on outline/brief intent broadly, not just the word "brief".

2026-07-035

content-distribution

siddiqss/semantic-seo-suite

Plan how a brand's published content gets seen — per-piece channel fit, repurposing atoms (X thread, LinkedIn post, Reddit answer, short-form video, newsletter), and a promotion cadence anchored to the publishing calendar. Use whenever the user asks how to promote or distribute content, repurpose a post, where to share an article, build a launch or content-promotion plan, drive traffic before SEO kicks in, or "we published it, now what". Matches channels to the brand's real personas; invents no reach numbers. Triggers on distribution / promotion / repurposing intent broadly.

2026-07-035

link-opportunities

siddiqss/semantic-seo-suite

Plan off-page authority for a brand — find and prioritize backlink opportunities from its topical map and competitor set, with a safe anchor-text mix and a competitor backlink-gap worksheet. Use whenever the user mentions backlinks, link building, off-page SEO, domain authority, digital PR, guest posts, "who should link to us", getting into best-of listicles, or why competitors outrank despite thinner content. Discovers real prospects via web_search (T1) or DataForSEO backlinks (T2); never invents authority numbers, referring domains, or contact emails. Triggers on off-page / link intent broadly.

2026-07-035

linking-and-schema

siddiqss/semantic-seo-suite

Generate an internal-linking plan and JSON-LD structured data from a brand's topical map and entity profile. Use whenever the user asks about internal links, anchor text, site structure, linking strategy, schema markup, structured data, or JSON-LD — or right after new content is drafted or published. Produces an actionable link checklist (with varied anchors) and validated per-node schema files. Triggers on linking/schema intent broadly.

2026-07-035

semantic-draft-writer

siddiqss/semantic-seo-suite

Write a full article draft from a semantic-SEO brief, following the micro-semantics writing rules and the brand's locked facts, then validate-and-repair it against the fabrication guard. Use whenever the user says "write the article", "draft from this brief", "turn this node into content", or asks to produce the actual copy for a topical-map node. Always runs scripts/validate_draft.py and repairs violations before returning. Triggers on drafting/writing intent for mapped content.

2026-07-035

name

semantic-site-auditor

description

semantic-site-auditor

Preconditions

brands/<slug>/config.yaml (tier).
A topical-map.json to audit against. If none exists, run topical-map-builder first (you can't measure coverage without a target map).
entity-profile.json (for the claimed-identity centroid used by drift).

Workflow

Crawl + extract the site into brands/<slug>/data/crawl/:
```
python ../../scripts/crawl_sitemap.py --domain <domain> --max-pages 500 --out /tmp/urls.json
python ../../scripts/extract_page_content.py --urls /tmp/urls.json --out-dir brands/<slug>/data/crawl
```
Robustness: crawl_sitemap.py falls back to a same-domain BFS when there's no sitemap, respects robots.txt, and caps pages/depth. For JS-rendered sites, extraction may be thin — note that in the report rather than treating missing content as a gap.
Run the analysis engine:
```
python ../../scripts/audit_site.py \
  --map brands/<slug>/topical-map.json --crawl-dir brands/<slug>/data/crawl \
  --entity-profile brands/<slug>/entity-profile.json \
  --locked brands/<slug>/locked-facts.json --brand "<Brand>" \
  --out brands/<slug>/audits/<date>-full.md
```
It matches each page to its nearest map node (embedding cosine) and reports:
- Coverage gaps — nodes with no matching page (derived).
- Cannibalization — page pairs with high similarity + same intent, and any node hit by multiple pages (derived).
- Entity drift — pages farthest from the core-section centroid, i.e. content pulling the site away from its claimed identity (derived). At T0 (no embeddings), do this qualitatively and label it asserted — never emit a fake distance.
- Orphans — pages with no incoming internal links (measured from the crawl link graph).
- Micro-audit — per-page lint (naked stats, fluff, unanswered question headings) reusing the draft rules.
Review + prioritise. The report ends with a prioritised action list: create (gap), consolidate/redirect (cannibalization), rewrite/relink or prune (drift), relink (orphan). Sanity-check each finding — with the offline hash-fallback embeddings, similarities are coarse; re-run with a model backend before making irreversible calls (redirects/prunes).
Feed back into the map. Apply status_updates from the audit JSON (matched nodes → published with their URL); mark thin/drifting matched nodes needs-update; add the confirmed gaps to calendar.md as new priorities.
Render the heatmap (../../scripts/map_heatmap.py) after status updates so coverage is visible at a glance.

Definition of done

Report produced with all five finding types, each provenance-tagged.
At least one finding is verifiable by hand (a true gap or a true cannibalization pair).
Map statuses updated; gaps flowed into the calendar.
No fabricated scores anywhere (drift/cannibalization are derived or clearly asserted).

Grounding ladder

T0: crawl + extract still work (they're just HTTP); matching/cannibalization/drift are LLM-qualitative and labeled asserted. Orphans + micro-audit are measured.
T1: embedding-based matching/cannibalization/drift (derived) — the real version.
T1+GSC: confirm cannibalization with pages sharing top queries in Search Console (the strongest, measured signal) — see seo-performance-tracker.