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.
npx skills add joaoguirunas/team-os --skill seo-schemagit clone --depth 1 https://github.com/joaoguirunas/team-osWrote 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.
[](https://agentmods.dev/skills/joaoguirunas/team-os/seo-schema)<a href="https://agentmods.dev/skills/joaoguirunas/team-os/seo-schema"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/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.
<a href="https://agentmods.dev/skills/joaoguirunas/team-os/seo-schema"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/seo-schema.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.01579 |
| Opus 5.5 | $0.00018 | $0.00632 |
| Sonnet 5.5 | $0.00009 | $0.00316 |
| Haiku 4.5 | $0.00004 | $0.00158 |
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 20d 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.
This is a copy
97% identical to seo-schema — 25 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Schema Markup Analysis & Generation
Detection
- Scan page source for JSON-LD
<script type="application/ld+json"> - Check for Microdata (
itemscope,itemprop) - Check for RDFa (
typeof,property) - Always recommend JSON-LD as primary format (Google's stated preference)
Validation
- Check required properties per schema type
- Validate against Google's supported rich result types
- Test for common errors:
- Missing @context
- Invalid @type
- Wrong data types
- Placeholder text
- Relative URLs (should be absolute)
- Invalid date formats
- Flag deprecated types (see below)
Schema Type Status (as of June 2026)
Read ../seo/references/schema-types.md for the full list. Key rules:
ACTIVE (recommend freely):
Organization, LocalBusiness, SoftwareApplication, WebApplication, Product (with Certification markup as of April 2025), ProductGroup, Offer, Service, Article, BlogPosting, NewsArticle, Review, AggregateRating, BreadcrumbList, WebSite, WebPage, Person, ProfilePage, ContactPage, VideoObject, ImageObject, Event, JobPosting, Course, DiscussionForumPosting
VIDEO & SPECIALIZED (recommend freely):
BroadcastEvent, Clip, SeekToAction, SoftwareSourceCode
See schema/templates.json for ready-to-use JSON-LD templates for these types.
JSON-LD and JavaScript rendering: Per Google's December 2025 JS SEO guidance, structured data injected via JavaScript may face delayed processing. For time-sensitive markup (especially Product, Offer), include JSON-LD in the initial server-rendered HTML.
NO RICH RESULTS, KEEP IF USEFUL:
- FAQPage: Google retired FAQ rich results for ALL sites on May 7, 2026 (supersedes the Aug 2023 gov/health restriction). No Google SERP rich-result benefit; flag existing FAQPage at Info (not Critical) rather than removal. For genuine user Q&A pages, use QAPage.
DEPRECATED (never recommend):
- HowTo: Rich results removed September 2023
- SpecialAnnouncement: Deprecated July 31, 2025
- CourseInfo, EstimatedSalary, LearningVideo: Retired June 2025
- ClaimReview: Retired from rich results June 2025
- VehicleListing: Retired from rich results June 2025
- Practice Problem: Deprecation notice 2025-11-05; Search Console / Rich Results Test support removed 2026-01-06
- Book Actions: Deprecated/removed from Google rich results; do not recommend it for SERP features.
- Search Console / Rich Results Test / appearance-filter support for CourseInfo, EstimatedSalary, LearningVideo, SpecialAnnouncement, VehicleListing was removed 2025-09-09; Practice Problem support was removed 2026-01-06.
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.
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.
- 20d ago Changed · -1 lines 0256e9ce6076
- 25d ago First seen · 176 lines · 44 tokens per session scan A 67b0fa5004e7
seo-schema is a skill published in the GitHub repository joaoguirunas/team-os (4 stars, last pushed 2d ago), licensed MIT. It adds 44 tokens to every session and 1,579 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to seo-schema, differing in 25 lines, and is treated as a copy.
Other skills, from other repositories
jsonl-log-analyzer
Analyze large JSONL log files using schema-aware partitioned analysis. Discovers field schema, generates tailored jq extraction recipes, and orchestrates parallel chunk analysts with synthesis. Use when processing JSONL logs exceeding context limits, performing log analytics, or investigating incident logs.
orchestration-patterns
Apply proven orchestration patterns for agent teams including parallel specialists, pipelines, swarms, research+implementation, plan approval, and multi-file refactoring. Use when choosing a team structure, designing workflows, or implementing specific coordination patterns.
task-system
Manage shared task lists for agent teams including creating tasks, setting dependencies, claiming work, and tracking progress. Use when creating work items, building task pipelines, coordinating task ownership, or managing task dependencies.
spawn-backends
Configure how teammate agents run including in-process, tmux, and iTerm2 backends. Use when choosing a display mode, setting up split panes, troubleshooting backend issues, or configuring teammateMode.
error-handling
Debug and recover from agent team errors including common errors, hooks for quality gates, known limitations, and recovery strategies. Use when encountering team errors, enforcing quality gates with hooks, understanding limitations, or debugging agent issues.
messaging
Send messages between agents using SendMessage including direct messages, broadcasts, shutdown requests/responses, and plan approvals. Use when communicating between agents, understanding message formats, or handling structured protocol messages.