Seo Brand Foundation

seo-brand-foundation

Produce a rigorous, provenance-tagged foundation that everything downstream depends on. Getting the central entity and core/outer boundary right here is worth more than any later cleverness — a perfect map of the wrong site is still wrong.

Read ../../framework/source-context.md and ../../framework/eav-modeling.md before starting. Read ../../framework/00-overview.md if you haven't this session (it sets the provenance rules you must follow).

Inputs

• Brand domain + niche (from the user).
• brands//config.yaml — read it first for grounding tier and sources.

Workflow

1. Load config. Determine tier. Everything below adapts to what's enabled.

1. Understand the current site (if it exists).

• T1 (crawl: true): run ../../scripts/crawl_sitemap.py then

../../scripts/extract_page_content.py on home, about, product/pricing, and the top few content pages to infer what the site currently claims to be. Record as measured (crawl).

• T0: web_search the brand + fetch the homepage to infer the same, labeled

asserted where you're inferring.

1. Resolve the central entity.

• Distinguish it from the brand name — it's what the brand is about (see

source-context.md "brand-as-central-entity" failure mode).

• T1 (wikidata: true): ../../scripts/wikidata_entity.py to get canonical typing
• a real attribute set (measured). T0: type it by judgement (asserted).

1. Write source context + central intent. What the brand is, who for, how it

monetizes, and the one intent it exists to satisfy. Derive the core/outer boundary from monetization (source-context.md). If you can't cleanly classify a topic as core or outer later, the boundary here is under-specified — fix it now.

1. Personas + competitor entities. 2–4 personas (needs, sophistication).

Competitors via web_search (T0) or domain-competitor data (T2), each tagged.

1. Brand EAV attribute inventory. Decompose the brand's own offering into

attributes (defining/unique/rare/common) per eav-modeling.md. Factual values here must be grounded — see step 7.

1. Seed locked-facts.json. For every concrete brand fact (price, spec, capability,

stat) you'd want articles to state: confirm it with the user or a cited source, then write it to brands//locked-facts.json with source + verified_date. If a fact isn't confirmed, it does NOT go in — and articles won't be allowed to state it. Ask the user to confirm brand facts; never invent them to fill the ledger.

1. Emit artifacts.

• brands//entity-profile.json — must validate against

../../templates/entity-profile.schema.json; every factual field provenance-tagged (use ../../scripts/provenance.py).

• brands//locked-facts.json — must validate against its schema.
• Append a one-page human-readable foundation summary to the workspace

(brands//foundation-summary.md).

Interview, don't assume

When information is missing (monetization details, what they refuse to cover, unverified specs), ask the user rather than guessing. The will-not-cover list and the monetization model are the two answers that most shape the map — get them explicitly.

Definition of done

• entity-profile.json validates; central entity is the subject, not the brand name.
• Core/outer boundary is stated as a rule you could apply to a new topic.
• locked-facts.json exists (may be small) with sources on every fact.
• No bare numbers anywhere: run provenance.audit() mentally / via the validator.

Grounding ladder

• T0: LLM + web_search; most fields asserted; entity typed by judgement.
• T1: + Wikidata typing (measured) + site crawl of claimed identity (measured).
• T2: + DataForSEO domain-competitor data for the competitor list (measured).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: siddiqss
• Source: siddiqss/semantic-seo-suite
• License: MIT

Install and usage instructions live in the source repository linked above.