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 shaom/infocard-skills --skill editorial-card-screenshotgit clone --depth 1 https://github.com/shaom/infocard-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/shaom/infocard-skills/editorial-card-screenshot)<a href="https://agentmods.dev/skills/shaom/infocard-skills/editorial-card-screenshot"><img src="https://agentmods.dev/badge/skills/shaom/infocard-skills/editorial-card-screenshot/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/shaom/infocard-skills/editorial-card-screenshot"><img src="https://agentmods.dev/badge/skills/shaom/infocard-skills/editorial-card-screenshot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00135 | $0.03308 |
| Opus 5.5 | $0.00054 | $0.01323 |
| Sonnet 5.5 | $0.00027 | $0.00662 |
| Haiku 4.5 | $0.00014 | $0.00331 |
Grade A, and why
editorial-card-screenshot 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- editorial-card-screenshot — 89% identical, 53 lines differ
How it starts
The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Editorial Card Screenshot
Overview
Turn source text into a compact, high-contrast HTML information card that follows the user's editorial prompt, then render a screenshot in one of the supported aspect ratios. The goal is not just density but editorial quality: clear hierarchy, strong visual anchors, and screenshot-stable rendering without accidental cropping or dead space.
Always preserve three output stages unless the user explicitly asks to skip one:
- Write one sentence judging the information density as high, medium, or low.
- Output the complete HTML with embedded CSS.
- Self-check that body text remains readable on mobile.
Workflow
1. Analyze Content Density
Read references/content-fit.md. Inventory semantic units, estimate density, and choose layout strategy from both density and ratio:
- Use "big-character" composition when content is sparse and a single phrase, number, or hook can carry the page.
- Use a two-column or three-column editorial grid when content is dense and needs stronger hierarchy.
- Use oversized numbers, heavy rules, tinted blocks, and pull-quote scale to avoid dead space.
- Do not force dense content into evenly weighted tiles. Build primary blocks, secondary blocks, and lighter supporting blocks.
- Match structure to content type:
- Ranking / recommendation content: allow asymmetric hero + structured list.
- Tutorial / analysis / interpretation content: group into overview, core judgment, interpretation, boundary, and conclusion.
- Write a short space-allocation plan before final HTML. Assign approximate area to hero, primary module, support area, and footer.
- Do not use the starter template's current arrangement as evidence that it is the right skeleton.
Before compressing content, first change the layout skeleton.
- Ratio changes should primarily change reading path, hierarchy, and module arrangement.
- Do not treat ratio changes as a reason to delete content by default.
- Only compress, group, or summarize when the current ratio cannot hold the content clearly after layout has already been restructured.
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.
- 1mo ago First seen · 258 lines · 135 tokens per session scan A 0ae39a886aaa
editorial-card-screenshot is a skill published in the GitHub repository shaom/infocard-skills (519 stars, last pushed 4mo ago), licensed MIT. It adds 135 tokens to every session and 3,308 once invoked, about $0.0005 per session on Opus 5.5. 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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