seo-schema

seo-schema is a skill for Claude Code, Codex from Orkas-AI/Orkas. It costs 2 tokens per session (704 once invoked), scanned A, original, MIT.

A tool for checking and creating JSON-LD, a machine-readable description of webpage content used by search engines. It examines existing structured data and can produce a template for a chosen schema type.

In plain words
What is it for?
Use it to validate page schema, review detected schema types, get recommendations, or generate a paste-ready template such as an Organization record.
Why use it?
It finds errors or missing fields in structured data and indicates which schema types a page may need. It works from crawl data and does not access the network.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to validate page schema, review detected schema types, get recommendations, or generate a paste-ready template such as an Organization record.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/orkas-ai/orkas/seo-schema
About the project

Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.

Orkas-AI/Orkas · 1,848 stars · on GitHub · orkas.ai

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 Orkas-AI/Orkas --skill seo-schema
Clone the repo
git clone --depth 1 https://github.com/Orkas-AI/Orkas

Made for: Claude Code, 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 seo-schema

README.md
[![agentmods](https://agentmods.dev/badge/skills/orkas-ai/orkas/seo-schema/github.svg)](https://agentmods.dev/skills/orkas-ai/orkas/seo-schema)
Your own site
<a href="https://agentmods.dev/skills/orkas-ai/orkas/seo-schema"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/seo-schema/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-schema

Your own site · 80×15
<a href="https://agentmods.dev/skills/orkas-ai/orkas/seo-schema"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/seo-schema.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 2 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 704 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00002 $0.00704
Opus 5 $0.00001 $0.00352
Sonnet 5 $0.00000 $0.00141
Haiku 4.5 $0.00000 $0.00070

Measured 10d ago against content hash 2c12100e17bb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

seo-schema 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 10d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/schema.py, test/test_schema.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

resources/builtin/marketplace/agents/e064dca9e1bd/skills/seo-schema/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

seo-schema

Lint existing JSON-LD and generate templates. Pure analysis/templating — no network.

When to use

  • The diagnose flow wants structured-data findings + which schema types the page should add.
  • The apply/content flow needs a paste-ready JSON-LD snippet for a type.

When NOT to use

  • Coarse "has any structured data?" — seo-tech-audit already flags that. This goes deeper (per-node lint, recommendations, generation).
  • Writing the JSON-LD into source — the agent does that (with this skill's generated snippet).

Preconditions

  • For validate: a seo-crawl JSON (uses each page's parsed structured_data). Python 3.9+ stdlib only.

How to call

Validate existing JSON-LD + recommend types:

"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" seo-schema schema -- --op validate --input <crawl.json> [--out <schema.json>]

Generate a template (for apply/content mode):

"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" seo-schema schema -- --op generate --type Organization [--json '{"name":"Orkas","url":"https://orkas.ai"}']

Expected output

validate:

{ "ok": true, "data": {
  "schema_score": 96, "present_types": ["Organization"], "recommended_types": ["WebSite"],
  "findings": [ { "id": "schema_recommend", "dimension": "schema", "severity": "low", ... } ],
  "summary": { "total": 1 }, "meta": { "url": "..." } } }

Findings use dimension: "schema" and feed seo-report --add.

generate: { "ok": true, "data": { "jsonld": { "@context": "https://schema.org", "@type": "Organization", ... } } }. Emit the jsonld object as a <script type="application/ld+json"> block; the JSON-LD must match the visible page one-to-one (esp. FAQ Q&A). Failure: {"ok": false, "error": "..."}, non-zero exit.

Lint coverage

Missing @type; missing required fields (Organization/WebSite/SoftwareApplication/Article/FAQPage/BreadcrumbList/Product/HowTo); deprecated rich-result types (FAQPage/HowTo still valid markup but no rich result for most sites); recommended types by page role (home → Organization+WebSite; deep page → BreadcrumbList). @graph is expanded.

Read the full file on GitHub · 54 lines

Files

What ships with it

2 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. 10d ago First seen · 54 lines · 2 tokens per session scan A 2c12100e17bb

Subscribe to this mod's changes

seo-schema is a skill published in the GitHub repository Orkas-AI/Orkas (1,848 stars, last pushed yesterday), licensed MIT. It adds 2 tokens to every session and 704 once invoked, about $0.0000 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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