SEO Geo
ReScienceLab/opc-skills
SEO & GEO (Generative Engine Optimization) for websites. An agent skill from ReScienceLab/opc-skills.
Implement Schema.org structured data markup in JSON-LD format for enhanced search results.
Install Algo SEO Schema
$ npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install asgard-ai-platform/skills algo-seo-schema --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/algo-seo-schema .claude/skills/algo-seo-schema && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "algo-seo-schema" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-seo-schema into .claude/skills/algo-seo-schema/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-seo-schema", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/asgard-ai-platform/skills/tree/main/algo-seo-schemaType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install asgard-ai-platform/skills algo-seo-schema --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/algo-seo-schema .agents/skills/algo-seo-schema && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "algo-seo-schema" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-seo-schema into .agents/skills/algo-seo-schema/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-seo-schema", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install asgard-ai-platform/skills algo-seo-schema --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/algo-seo-schema .cursor/skills/algo-seo-schema && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "algo-seo-schema" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-seo-schema into .cursor/skills/algo-seo-schema/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-seo-schema", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/asgard-ai-platform/skills.git --path algo-seo-schema--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install asgard-ai-platform/skills algo-seo-schema --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/algo-seo-schema .gemini/skills/algo-seo-schema && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "algo-seo-schema" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-seo-schema into .gemini/skills/algo-seo-schema/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-seo-schema", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install asgard-ai-platform/skills algo-seo-schemaInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/algo-seo-schema .github/skills/algo-seo-schema && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "algo-seo-schema" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-seo-schema into .github/skills/algo-seo-schema/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-seo-schema", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install asgard-ai-platform/skills algo-seo-schema --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/algo-seo-schema .opencode/skills/algo-seo-schema && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "algo-seo-schema" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-seo-schema into .opencode/skills/algo-seo-schema/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-seo-schema", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
algo-seo-schema- GitHub stars
- 242
- Token cost
- ~966 tokens
- SKILL.md length
- 387 words
- Files
- 4 (incl. references)
- Skills in repo
- 207
- Repo updated
- First seen
- Licence
- MIT
At a glance
Implement Schema.org structured data markup in JSON-LD format for enhanced search results.
- Works in 4 steps: Input Validation → Core Algorithm → Verification → …
- The user needs to add rich snippets to web pages
- SKILL.md covers Overview, When to Use, Algorithm and Output Format, plus 3 more sections
- Reaches schema.org
What it does
Algo SEO Schema is an agent skill from asgard-ai-platform/skills. Implement Schema.org structured data markup in JSON-LD format for enhanced search results. Use this skill when the user needs to add rich snippets to web pages, implement FAQ/Product/Article schema, or validate structured data — even if they say 'rich snippets', 'structured data', or 'Google rich results'.
Its SKILL.md is about 970 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `examples/sample_scenario.md`, `references/type-properties.md` and `references/validation-errors.md`).
It sits in Marketing & SEO, covering Schema markup. The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.
When your agent uses it
- The user needs to add rich snippets to web pages
- Implement FAQ/Product/Article schema
- Validate structured data — even if they say rich snippets
- Structured data
Example prompts
- “rich snippets”
- “structured data”
- “Google rich results”
- “/algo-seo-schema”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
schema.org
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Algo SEO Schema loads about 966 tokens when it runs, and up to ~6.7k if it reads all its reference files. Until then it costs about 81 tokens; SKILL.md has 387 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 387 words, ~966 tokens.
Download SKILL.mdSave it as
.claude/skills/algo-seo-schema/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- algo-seo-schema
- description
- Implement Schema.org structured data markup in JSON-LD format for enhanced search results. Use this skill when the user needs to add rich snippets to web pages, implement FAQ/Product/Article schema, or validate structured data — even if they say 'rich snippets', 'structured data', or 'Google rich results'.
- metadata.category
- WP-35 SEO 演算法
- metadata.tags
- seo, schema-org, json-ld, structured-data
Schema.org Structured Data
Overview
Schema.org structured data provides machine-readable page context to search engines via JSON-LD. Enables rich results (stars, FAQs, breadcrumbs, product cards) in SERPs. Implementation is O(1) per page — it's a markup task, not computational.
When to Use
Trigger conditions:
- Adding rich snippet eligibility to web pages
- Implementing product, article, FAQ, HowTo, or event markup
- Debugging Google Search Console structured data errors
When NOT to use:
- When optimizing page content or keywords (use content SEO)
- When improving page speed (use Core Web Vitals optimization)
Algorithm
IRON LAW: Schema Markup Must MATCH Visible Content
Marking up content that users can't see violates Google guidelines
and risks manual penalties. Every structured data field must
correspond to content visible on the page.Phase 1: Input Validation
Identify page type (Article, Product, FAQ, HowTo, Event, etc.). Map visible content to required and recommended schema properties. Gate: Page type identified, all required properties have visible content.
Phase 2: Core Algorithm
- Select the correct Schema.org type from the vocabulary
- Map page content to schema properties (name, description, image, etc.)
- Build JSON-LD object with @context and @type
- Handle nested types (e.g., Product contains Offer contains Price)
- Place JSON-LD in
<script type="application/ld+json">in<head>
Phase 3: Verification
Validate with Google Rich Results Test. Check: no errors, all required fields present, no mismatch with visible content. Gate: Passes Google Rich Results Test with zero errors.
Phase 4: Output
Return complete JSON-LD markup ready for insertion.
Output Format
{
"schema": {"@context": "https://schema.org", "@type": "Product", "name": "...", "offers": {"@type": "Offer", "price": "29.99", "priceCurrency": "TWD"}},
"validation": {"errors": 0, "warnings": 1, "eligible_rich_results": ["Product snippet"]}
}Examples
Sample I/O
Input: FAQ page with 3 questions and answers Expected: FAQPage schema with 3 Question/Answer pairs in JSON-LD
Show full SKILL.md (156 more words)Show less
Edge Cases
| Input | Expected | Why |
|---|---|---|
| Page with no clear type | Use WebPage as fallback | Most generic valid type |
| Multiple schemas needed | Array of JSON-LD objects | One page can have multiple types |
| Missing required field | Error, do not generate | Incomplete schema hurts more than none |
Gotchas
- Required vs recommended: Google requires certain fields per type. Missing required fields = schema ignored entirely. Check documentation per type.
- Nesting depth: Deeply nested schemas (Product > Offer > Seller > Address) are error-prone. Validate each nesting level.
- Schema spam: Adding schema for content not on the page (fake reviews, unavailable prices) triggers manual actions.
- Type specificity: Use the most specific type available. "Article" is better than "WebPage"; "NewsArticle" is better than "Article" for news content.
- Testing gap: Google Rich Results Test shows what Google sees, but not all valid schema triggers rich results. Eligibility ≠ guarantee of display.
References
- For complete property reference by type, see
references/type-properties.md - For common validation errors and fixes, see
references/validation-errors.md
© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in algo-seo-schema of asgard-ai-platform/skills.
- SKILL.md
- examples/sample_scenario.md
- references/type-properties.md
- references/validation-errors.md
Open the folder on GitHubat commit 4e7f4f8
Compare with similar skills
Algo SEO Schema next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Algo SEO Schema this skillasgard-ai-platform/skills | 242 | — | ~966 | Automated safety check: Pass | MIT | |
| SEO GeoReScienceLab/opc-skills | 1.8k | 4 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude | 11k | — | ~2.8k | Automated safety check: Notes | MIT | |
| SEO Optimizerailabs-393/ai-labs-claude-skills | 455 | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Portaljs Add Dcatdatopian/portaljs | 2.4k | 1 repos | ~1.8k | Automated safety check: Pass | MIT | |
| Schema Markupfreekmurze/dotfiles | 1k | 15 repos | ~1.2k | Automated safety check: Pass | None |
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Related
Categories
Questions about Algo SEO Schema
What does Algo SEO Schema do?
Implement Schema.org structured data markup in JSON-LD format for enhanced search results. Algo SEO Schema is an agent skill from asgard-ai-platform/skills.org structured data markup in JSON-LD format for enhanced search results.
When should I use Algo SEO Schema?
Algo SEO Schema fits situations like: the user needs to add rich snippets to web pages; implement FAQ/Product/Article schema; validate structured data — even if they say rich snippets; structured data.
How do I install Algo SEO Schema in Claude Code?
Run `npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a claude-code`. Or copy the skill folder (algo-seo-schema in asgard-ai-platform/skills) into .claude/skills/algo-seo-schema in your project. Claude Code loads it when a task matches its description.
How do I install Algo SEO Schema in Codex?
Run `npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a codex`. Or copy the skill folder (algo-seo-schema in asgard-ai-platform/skills) into .agents/skills/algo-seo-schema in your project. Codex loads it when a task matches its description.
Can I use Algo SEO Schema in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgard-ai-platform/skills --skill algo-seo-schema -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/algo-seo-schema, .gemini/skills/algo-seo-schema, .github/skills/algo-seo-schema and .opencode/skills/algo-seo-schema in your project.
What does Algo SEO Schema need to run?
SKILL.md names no scripts, command-line tools or credentials: Algo SEO Schema is instructions for the agent only.
Does Algo SEO Schema access the network?
SKILL.md names 1 domain. In commands or code: schema.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Algo SEO Schema safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Algo SEO Schema use?
Algo SEO Schema is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Algo SEO Schema use?
About 966 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.7k tokens, read only when the agent opens those files.
What are the alternatives to Algo SEO Schema?
Skills that share tags, products or a category with Algo SEO Schema: SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars), SEO Optimizer (ailabs-393/ai-labs-claude-skills, 455 stars) and Portaljs Add Dcat (datopian/portaljs, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Algo SEO Schema?
asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.
Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.