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 JakeLabate/Claude-SEO-Skills --skill open-graph-auditgit clone --depth 1 https://github.com/JakeLabate/Claude-SEO-SkillsWrote 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/jakelabate/claude-seo-skills/open-graph-audit)<a href="https://agentmods.dev/skills/jakelabate/claude-seo-skills/open-graph-audit"><img src="https://agentmods.dev/badge/skills/jakelabate/claude-seo-skills/open-graph-audit/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/jakelabate/claude-seo-skills/open-graph-audit"><img src="https://agentmods.dev/badge/skills/jakelabate/claude-seo-skills/open-graph-audit.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 | $0.00130 | $0.01250 |
| Opus 5 | $0.00065 | $0.00625 |
| Sonnet 5 | $0.00026 | $0.00250 |
| Haiku 4.5 | $0.00013 | $0.00125 |
Grade A, and why
open-graph-audit 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open Graph / Social Metadata Audit
Audit a website's Open Graph and Twitter Card tags and produce an actionable report on how the site's links render when shared.
When to use this skill
Use this skill when the user asks to:
- Audit, validate, or check Open Graph (
og:*) or Twitter Card (twitter:*) tags - Diagnose why links look wrong / have no image when shared on social or chat
- Find missing or broken share images, or
og:urlthat points at the wrong URL - Improve social click-through and link previews
Inputs to collect
- Site URL or URL list — a live site root to crawl (auto-seeds from
/sitemap.xml), or a text file with--url-list. - Scope — pages to crawl (default 500,
--max-pages). - Image probing — whether to probe each
og:image/twitter:imagefor status and content type (default on;--no-probeto skip).
Workflow
Step 1: Crawl and probe social tags
Use scripts/extract_social.py:
python3 scripts/extract_social.py https://example.com --max-pages 500 --output social_inventory.json
# already crawled once (e.g. in a full SEO audit)? skip the crawl and reuse the shared cache:
# python3 scripts/fetch_pages.py https://example.com --output page_cache.json
# python3 scripts/extract_social.py --from-cache page_cache.json --output social_inventory.json
It records each page's OG and Twitter Card tags, canonical, and meta robots, then probes each unique share image for HTTP status and content type.
Step 2: Run the audit checks
python3 scripts/audit_social.py social_inventory.json --output audit_report.json
Step 3: Evaluate the audit checks
Evaluate each check in references/audit-checks.md. Core checks:
| Check | Severity |
|---|---|
| Missing og:title | High |
| Missing og:image | High |
| Broken og:image (non-200) | High |
| Missing og:description | Medium |
| Missing og:url | Medium |
| og:url mismatches canonical | Medium |
| og:image not an image / relative | Medium |
| Missing twitter:card (no OG fallback) | Low |
| og:title / og:description too long | Low |
| Duplicate/default share image across many pages | Info |
What ships with it
7 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.
- 11d ago First seen · 114 lines · 0 tokens per session scan A d7fa364031e2
open-graph-audit is a skill published in the GitHub repository JakeLabate/Claude-SEO-Skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 130 tokens to every session and 1,250 once invoked, about $0.0006 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.
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