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 NatsuFox/Tapestry --skill visual-cardgit clone --depth 1 https://github.com/NatsuFox/TapestryWrote 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/natsufox/tapestry/visual-card)<a href="https://agentmods.dev/skills/natsufox/tapestry/visual-card"><img src="https://agentmods.dev/badge/skills/natsufox/tapestry/visual-card.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 | $0.00059 | $0.02319 |
| Opus 5 | $0.00030 | $0.01159 |
| Sonnet 5 | $0.00012 | $0.00464 |
| Haiku 4.5 | $0.00006 | $0.00232 |
Grade A, and why
visual-card 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 8d 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tapestry Visual Card
Generate professional visual note cards from knowledge base content: $ARGUMENTS
When to use this skill
Use this skill when:
- A user wants to create a visual note card or infographic from KB content
- The user asks to "visualize", "create a card", "make an infographic", or "generate a visual summary"
- The user mentions 视觉笔记, 知识卡片, 信息图, or one-pager summary
- You need to present knowledge base content in a shareable, poster-style format
- The user wants to export KB content for social media or presentations
Purpose
This skill transforms structured knowledge base content into beautiful, information-dense visual cards following an editorial magazine aesthetic. It produces:
- A self-contained HTML file with embedded styles and export functionality
- A high-quality PNG image (via Playwright rendering)
The cards follow a fixed layout structure optimized for readability and social sharing.
Workflow
Architecture: Agent-Driven Content Synthesis
This skill uses an Agent-driven approach where the Agent reads the template specification and autonomously decides how to map source content to template blocks.
Key principle: The template structure is fixed (7 display blocks), but content mapping is intelligent and adaptive.
Step 1: Identify the Source Content
Resolve the target from the argument:
- If a specific chapter path is provided (e.g., "ai-and-development-tools/ai-agent-architecture.md"), use that chapter
- If a topic is provided (e.g., "ai-and-development-tools"), offer to generate cards for its chapters
- If no argument, list available topics and ask the user to choose
# List available topics
ls -d data/books/*/
Step 2: Run the Context Preparation Script
python visual-card/_scripts/generate_card.py --chapter "<topic>/<chapter.md>"
This prints a JSON object with three keys:
source.content: the raw chapter markdownsource.frontmatter: parsed metadata (title, author, date, etc.)template_specification: full natural language spec of the 7 template blocksinstructions: task description
What ships with it
9 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.
- _scripts/generate_card_from_synthesis.py 10 KB runs code
- _scripts/generate_card_legacy.py 23 KB runs code
- _scripts/generate_card.py 2.3 KB runs code
- _scripts/html2png.py 3.3 KB runs code
- _scripts/prepare_card_context.py 4.6 KB runs code
- _templates/card_template_spec.md 10 KB
- _templates/card_template.html 23 KB
- AGENT_DRIVEN.md 6.8 KB
- README.md 1.6 KB
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.
- 8d ago First seen · 253 lines · 59 tokens per session scan A e37d78149e22
visual-card is a skill published in the GitHub repository NatsuFox/Tapestry (64 stars, last pushed 4mo ago), licensed MIT. It adds 59 tokens to every session and 2,319 once invoked, about $0.0003 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 2026-08-30.
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