/kai-seo-audit — Prioritized Technical Fix List

Kai root note: knowledge/, harness/, and scripts/ paths in this skill live in the Kai install, not the user's project. Resolve them against the first ancestor directory of this SKILL.md that contains a knowledge/ folder (the Kai plugin root, ~/.claude/kai, or the kai-cmo-harness repo). MARKETING.md, memory/, and any output files live in the current project. If a referenced scripts/ command is not available in this install, say so, skip it, and continue with the file-based guidance — never fabricate its output.

Objective

A client-facing audit of one site in which every finding is traceable to a retrieved artifact, ordered so the reader knows what to fix first and what it costs. The deliverable states its audit mode, carries a health score computed only from observed checks, lists P0 through P3 fixes with pages affected, and names the access or exports that would remove the remaining uncertainty.

An audit whose numbers cannot be traced back to a collector run is worse than no audit — it moves budget on invented evidence.

Done when

Work type audit-report — floor E3/C4/O1 (harness/eco-floors.yaml).

• E3 — a named human approved the exact delivered file, hash-pinned, and every quantitative claim in it resolves to a collector source in workspace/seo-audit/.
• C4 — the Kai Data Provenance Rule is satisfied: collector run before writing, mode declared, a collector source cited for every number, missing data in _data-gaps.md. banned_word_check and audit_provenance_lint both pass.
• O1 — every P0 recommendation names the metric it targets, with a baseline, a threshold, and an owner. Adoption and effect are read at 60 days.

python scripts/quality_gates/audit_provenance_lint.py workspace/seo-audit --audit-dir

Constraints

Kai Data Provenance Rule (non-negotiable). Load harness/references/audit-data-provenance.md before writing any finding. Declare one mode:

• sales_external — public-only or prospect audits.
• onboarding_connected — GSC, GA4, GBP, crawl exports, or SEO platform data are connected.
• internal_demo — values are placeholders and labeled as such.

Run the collector before writing. It is shared by all Kai workflows, not audit-only; this audit consumes the audit-data.json alias. Existing audit automations may keep using python -m scripts.audit.collect; non-audit SEO workflows should prefer python -m kai.source_data.collect and read kai-data.json.

python -m scripts.audit.collect --url "<url>" --mode sales_external --workflow seo-audit --out workspace/seo-audit --pagespeed --dataforseo --seo-provider auto --keywords "<kw1>,<kw2>" --location "<city, state>"

python -m scripts.audit.collect --url "<url>" --mode onboarding_connected --workflow seo-audit --out workspace/seo-audit --pagespeed --places --dataforseo --seo-provider auto --gsc --ga4 --keywords "<kw1>,<kw2>" --location "<city, state>" --date-from "<YYYY-MM-DD>" --date-to "<YYYY-MM-DD>"

Add --third-party-sources serpapi,brightlocal,similarweb,builtwith,wappalyzer,bing-webmaster when licensed vendor or non-Google search data is needed. API vendor values are third_party_estimate; supplied exports are user_provided.

• Never publish without source, retrieval date, and artifact/API note: rankings, traffic, clicks, CTR, Core Web Vitals, PageSpeed, indexed-page counts, backlinks, Domain Rating, AI Overview visibility, schema validity, local pack placement. If the metric is absent from workspace/seo-audit/audit-data.json, it is a data gap, not an estimate.
• Every check carries source metadata:

source_tier: connected | public_observed | user_provided | inferred | missing_data
source_name: ""
source_url: ""
retrieved_at: ""
evidence_artifact: ""
confidence: high | medium | low
score_eligible: true | false

• inferred and missing_data items are excluded from the health score.
• Agent-readiness gate. Site-level SEO/AEO work audits the domain against knowledge/checklists/agent-readiness-checklist.md before recommending outbound work; run python scripts/quality_gates/agent_readiness_lint.py https://<domain>. Any P0 failure blocks the plan. Treat llms.txt as useful for cooperative agents, not a Google AI Overview ranking requirement.
• Read MARKETING.md from the project root before asking the user anything. If it does not exist, build it from the codebase — README, manifests, landing pages, route files, analytics and email config — and confirm the draft.
• No live mutation. The audit recommends; it does not change robots.txt, sitemaps, tags, or redirects.

Priority scoring — the impact/effort matrix that orders the fix list:

Priority	Impact	Effort	Examples
P0	High	< 1 hour	Missing title tags, broken canonical, noindex on important pages
P1	High	1 day	CWV failures, redirect chains, thin content
P2	Medium	1 week	Schema markup, internal linking optimization
P3	Low / nice-to-have	Ongoing	Alt text gaps, URL cleanup

Context

Six things must be known before the audit is scoped: the URL, the scope (full site or sections), any known issues already flagged, whether Search Console and analytics access exists, what matters most (rankings, traffic, indexation, speed), and which data sources are available — public crawl, PageSpeed Insights, DataForSEO, Ahrefs/Semrush/Moz, GSC, GA4, GBP, Screaming Frog/Sitebulb export. MARKETING.md answers most of them.

Need	Load
Audit procedure and coverage	knowledge/checklists/technical-seo-audit-sop.md
Technical check detail	knowledge/checklists/technical-seo-checklist.md
SEO validation rules	knowledge/checklists/seo-checklist.md
Provenance modes, source tiers, data-gap handling	harness/references/audit-data-provenance.md
Agent legibility rubric	knowledge/checklists/agent-readiness-checklist.md
Indexation troubleshooting	harness/references/google-indexation-monitoring.md
Product, ICP, current channels	MARKETING.md (project root)

Audit layers — the coverage the report must account for, each finding either observed or logged as a gap:

1. Crawlability & indexation — robots.txt blocks, XML sitemap presence/submission/freshness, canonical correctness and consistency, unintended noindex/nofollow, HTTP status codes (404s, redirect chains, 5xx), pagination handling.
2. Technical performance — Core Web Vitals (LCP, INP, CLS), mobile-friendliness, server response time and render-blocking resources, HTTPS mixed content and certificates, structured data presence and validity.
3. On-page — title tags (unique, keyword-included, under 60 chars), meta descriptions (unique, under 155 chars), one relevant H1 per page, descriptive image alt text, internal linking (orphan pages, link depth), URL structure.
4. Content quality — thin pages under 300 words, internal and external duplication, keyword cannibalization, freshness/last-updated, E-E-A-T signals (author bios, citations, credentials).
5. Off-page — backlink profile where data exists, unlinked brand mentions, local SEO (GBP, NAP consistency) where applicable.

Use the browse/gstack skill to crawl pages when available; otherwise work from what the user provides or can check, and mark the difference.

Recurring SEO ops monitor. For retained or repeated work, write seo-ops-monitor.md beside the report: weekly cadence for crawl/indexation/CWV/schema regressions, monthly for content decay, query movement, and internal-link opportunities. Inputs are collector output, GSC/GA4 exports when connected, PageSpeed artifacts, crawl exports, sitemap and robots snapshots, and licensed rank or local vendor exports. Alert rules: new noindex, robots block, sitemap drop, 4xx/5xx spike, redirect chain, canonical conflict, CWV regression, schema error, title/H1 removal, orphaned priority page, organic landing-page drop. Queue format: issue, source, retrieved_at, affected URL, severity, owner, proposed fix, approval needed, status, next check date. Movement, traffic, rankings, and visibility never appear without provenance; missing connected data is a monitor gap.

Output goes to workspace/seo-audit/[domain].md, stating audit mode, health score, P0–P3 tables with pages affected and fixes, checklist pass/fail results, top recommendations by impact-to-effort, a data-source inventory with retrieval dates and artifacts, and the data gaps that limit confidence. Same path as v1 — downstream tooling does not branch on version.

Escalate when

• The site cannot be crawled and no export or connected data is available — say so rather than auditing from assumption.
• Search Console or analytics access is claimed but the collector cannot reach it.
• A finding depends on a metric that exists in no source available at the declared mode.
• The declared mode does not match the data actually in hand (for example, onboarding_connected with no GSC pull).
• An agent-readiness P0 failure exists — the fix list stops there until it is resolved.
• A recommended fix carries migration, legal, or revenue risk (domain moves, mass redirects, noindexing live templates).