semantic-core-architect

semantic-core-architect is a skill for Codex from sergekostenchuk/seo-llm-skill-cluster. It costs 93 tokens per session (839 once invoked), scanned A, original, MIT.

A skill for organizing what a website should cover, who it serves, and what people are trying to find.

In plain words
What is it for?
Use it to build query clusters, audience and job maps, entity and topic maps, language priorities, evidence labels, and handoff material for information architecture.
Why use it?
It separates observed facts from assumptions and unknowns before page structure or content decisions are made. A semantic core is a structured map of topics, entities, audiences, and search intents.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 <codex-skills-dir>/senior-skill-architect/scripts/lint_production_skill.py ./skills/semantic-core-architect.

Good fit Use it to build query clusters, audience and job maps, entity and topic maps, language priorities, evidence labels, and handoff material for information architecture.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/sergekostenchuk/seo-llm-skill-cluster
agentmods
npx agentmods add skills/sergekostenchuk/seo-llm-skill-cluster/semantic-core-architect

Made for: Codex.

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 semantic-core-architect

README.md
[![agentmods](https://agentmods.dev/badge/skills/sergekostenchuk/seo-llm-skill-cluster/semantic-core-architect/github.svg)](https://agentmods.dev/skills/sergekostenchuk/seo-llm-skill-cluster/semantic-core-architect)
Your own site
<a href="https://agentmods.dev/skills/sergekostenchuk/seo-llm-skill-cluster/semantic-core-architect"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/seo-llm-skill-cluster/semantic-core-architect/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 semantic-core-architect

Your own site · 80×15
<a href="https://agentmods.dev/skills/sergekostenchuk/seo-llm-skill-cluster/semantic-core-architect"><img src="https://agentmods.dev/badge/skills/sergekostenchuk/seo-llm-skill-cluster/semantic-core-architect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 839 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 $0.00093 $0.00839
Opus 5 $0.00046 $0.00419
Sonnet 5 $0.00019 $0.00168
Haiku 4.5 $0.00009 $0.00084

Measured 11d ago against content hash 75fd96e945ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

semantic-core-architect 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 11d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/semantic-core-architect/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Semantic Core Architect

Use this skill before URL architecture, internal linking, schema, content planning, or LLM-friendly page design. It turns a site goal into reusable semantic artifacts.

Read references/semantic-core-rubric.md before producing a full semantic core.

Owns

  • query clusters;
  • user/search intents;
  • audience and job-to-be-done mapping;
  • entity and topic mapping;
  • language and locale priority;
  • evidence labels and data gaps;
  • handoff to information architecture.

Does Not Own

  • final URL/canonical policy;
  • internal link graph;
  • schema implementation;
  • page copywriting;
  • rank guarantees;
  • external link placement.

Workflow

  1. Capture the goal, audience, markets, languages, content model, constraints, and forbidden areas.
  2. Separate observed facts, user-provided facts, inferred assumptions, and unknowns.
  3. Build query clusters by intent, not by keyword volume alone.
  4. Map entities and topics to likely canonical page candidates without deciding final URLs.
  5. Assign priority from strategic value, page feasibility, audience fit, and evidence strength.
  6. Mark volume, difficulty, competitive strength, and rank opportunity as unknown unless verified from an approved source.
  7. Produce semantic-core.yaml and entity-topic-map.yaml using the templates in assets/.
  8. Hand off to information-architecture-seo with gaps and assumptions explicit.

Evidence Rules

  • Search volume, difficulty, traffic, ranking, and assistant citation claims require current evidence.
  • If keyword tools, Search Console, rank trackers, logs, or assistant-monitoring data are unavailable, use unknown.
  • Current facts about search engines, AI crawlers, rich results, or platforms must follow the cluster freshness policy.
  • Do not use competitor pages as proof of volume unless they come with a measured source.

Priority Model

Use P0 only when a cluster is both central to the site's identity and needed by downstream architecture. Use P1 for important supporting clusters. Use P2 for useful expansion. Use P3 for backlog or speculative ideas.

Read the full file on GitHub · 93 lines

Files

What ships with it

6 files 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. 11d ago First seen · 93 lines · 93 tokens per session scan A 75fd96e945ce

Subscribe to this mod's changes

semantic-core-architect is a skill published in the GitHub repository sergekostenchuk/seo-llm-skill-cluster (39 stars, last pushed 3mo ago), licensed MIT. It adds 93 tokens to every session and 839 once invoked, about $0.0005 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 2026-08-30.

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