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seo-brand-foundation

seo-brand-foundation is a skill for Claude Code from siddiqss/semantic-seo-suite. It costs 138 tokens per session (1,112 once invoked), scanned A, original, MIT.

A workflow for defining a brand's search-engine identity, audience, competitors, attributes, and trusted facts before doing further SEO work.

In plain words
What is it for?
Onboarding a brand, examining its existing website, identifying its central entity, and preparing facts for content planning and site audits.
Why use it?
It creates a documented foundation so later SEO decisions are based on the site's claims and recorded sources.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the semantic-seo-suite plugin — 10 skills shipped together

not rated 9repo +2 2mo ago A scan 138 tokens original MIT

Good fit Onboarding a brand, examining its existing website, identifying its central entity, and preparing facts for content planning and site audits.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/siddiqss/semantic-seo-suite/seo-brand-foundation
View source ↗ siddiqss/semantic-seo-suite
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add siddiqss/semantic-seo-suite --skill seo-brand-foundation
Clone the repo
git clone --depth 1 https://github.com/siddiqss/semantic-seo-suite

Made for: Claude Code.

Or install semantic-seo-suite, the plugin that ships this one along with the rest of its 10 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for seo-brand-foundation

README.md
[![agentmods](https://agentmods.dev/badge/skills/siddiqss/semantic-seo-suite/seo-brand-foundation/github.svg)](https://agentmods.dev/skills/siddiqss/semantic-seo-suite/seo-brand-foundation)
Your own site
<a href="https://agentmods.dev/skills/siddiqss/semantic-seo-suite/seo-brand-foundation"><img src="https://agentmods.dev/badge/skills/siddiqss/semantic-seo-suite/seo-brand-foundation/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for seo-brand-foundation

Your own site · 80×15
<a href="https://agentmods.dev/skills/siddiqss/semantic-seo-suite/seo-brand-foundation"><img src="https://agentmods.dev/badge/skills/siddiqss/semantic-seo-suite/seo-brand-foundation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,112 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00138 $0.01112
Opus 5 $0.00069 $0.00556
Sonnet 5 $0.00028 $0.00222
Haiku 4.5 $0.00014 $0.00111

Measured 12d ago against content hash 87867db8465b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

seo-brand-foundation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/seo-brand-foundation/SKILL.md · 87 lines

How it starts

The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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/<slug>/config.yaml — read it first for grounding tier and sources.

Workflow

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

  2. 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.

  3. 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).

  4. 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.

  5. Personas + competitor entities. 2–4 personas (needs, sophistication). Competitors via web_search (T0) or domain-competitor data (T2), each tagged.

  6. 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.

Read the full file on GitHub · 87 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 87 lines · 138 tokens per session scan A 87867db8465b

Subscribe to this mod's changes

seo-brand-foundation is a skill published in the GitHub repository siddiqss/semantic-seo-suite (9 stars, last pushed 2mo ago), licensed MIT. It adds 138 tokens to every session and 1,112 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Claude CodeMarketing and SEOaeoclaude-skillscontent-marketinggenerative-engine-optimizationgeo
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