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 agentmods add skills/m-binimran/design-pack/og-imagenpx skills add m-binimran/design-pack --skill og-imagegit clone --depth 1 https://github.com/m-binimran/design-packWrote 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/m-binimran/design-pack/og-image)<a href="https://agentmods.dev/skills/m-binimran/design-pack/og-image"><img src="https://agentmods.dev/badge/skills/m-binimran/design-pack/og-image.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.00285 |
| Opus 5 | $0.00023 | $0.00143 |
| Sonnet 5 | $0.00009 | $0.00057 |
| Haiku 4.5 | $0.00005 | $0.00028 |
Grade A, and why
og-image 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 5d 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.
What it actually says
og-image
The image that represents a link everywhere it's shared. Small, legible, on-brand.
Process
- Canvas 1200x630 (1.91:1). Keep key content centered - platforms crop edges differently.
- Hierarchy: a short headline (large, legible), optional supporting line, logo, a simple background or hero. Don't cram - it renders small.
- Build via Canva (branded) or
image-generatefor the background, then place text. - Contrast: text must pass over the background (the
contrast-guardhook) - add a scrim if needed. - Export optimized PNG/JPG (< ~1MB), absolute-URL ready; name kebab-case.
Output
- The OG image (confirmed from the connector) + the exact dimensions and the optimized file, ready to wire to
og:image.
Guardrails
- Legible at small size; safe margins; on-brand. Optimized weight.
- Verify it actually renders in a preview tester before claiming done; confirm connector output is real.
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.
- 5d ago First seen · 24 lines · 45 tokens per session scan A ef3288deaf94
og-image is a skill published in the GitHub repository m-binimran/design-pack (3 stars, last pushed 2mo ago), licensed MIT. It adds 45 tokens to every session and 285 once invoked, about $0.0002 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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