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 All-The-Vibes/ATV-PaperBoard --skill render-artifactgit clone --depth 1 https://github.com/All-The-Vibes/ATV-PaperBoardWrote 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/all-the-vibes/atv-paperboard/render-artifact)<a href="https://agentmods.dev/skills/all-the-vibes/atv-paperboard/render-artifact"><img src="https://agentmods.dev/badge/skills/all-the-vibes/atv-paperboard/render-artifact/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/all-the-vibes/atv-paperboard/render-artifact"><img src="https://agentmods.dev/badge/skills/all-the-vibes/atv-paperboard/render-artifact.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 | $0.00062 | $0.00943 |
| Opus 5 | $0.00031 | $0.00472 |
| Sonnet 5 | $0.00012 | $0.00189 |
| Haiku 4.5 | $0.00006 | $0.00094 |
Grade A, and why
render-artifact 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 12d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-artifact
Converts structured LLM output into a beautiful, linted HTML artifact governed by a DESIGN.md.
Usage
paperboard render --input <path-or-> [--design <name|path|url>] [--tier atv|pico|daisy] [--no-open]
Tier selection
- Default:
atv— the dark designed-document tier; use for dashboards, reports, and any rich multi-section output. This is the right answer in almost all cases. pico/daisy— light-document tiers; pick only when the target audience explicitly wants a lightweight, framework-styled page.
When to invoke
- The user asks to "render" or "visualize" structured output (tables, dashboards, comparisons).
- A prior tool write produced a file that looks like a data artifact.
Steps
- Collect the input path (or pipe JSON/Markdown via stdin with
--input -). - Optionally specify
--design(starter name, path, or URL) and--tier(omit foratv). - Run the command; report the triple paths and slug from stdout.
- If
--no-openwas NOT passed and the environment is non-headless, the browser opens automatically.
Output
The command writes three files and prints their paths:
<slug>.html— single-file artifact<slug>.DESIGN.md— design sidecar<slug>.meta.yaml— metadata (tier, harness, lint_passed, created_at)
Input shape — pick the richest one that fits
The atv tier renders three distinct layouts depending on what --input receives.
Prefer the richest layout the content supports — most agent output is structured
enough to use the section graph, which is the only mode that exercises the
designed-document treatment (hero strip, numbered sections, accent typography).
1. Section graph — use this for almost everything
JSON with a top-level sections: [...] array. Each entry has a kind that maps
to one of 15 emitters. Run paperboard schema to see them all, or
paperboard schema --kind <name> for fields + an example payload.
{
"title": "Pipeline Report",
"sections": [
{"kind": "hero", "eyebrow": "Release", "title": "v0.2.0 pipeline.", "sub": "All checks green."},
{"kind": "sec", "num": "01", "title": "Build matrix.",
"body": [{"kind": "status-table", "rows": [{"check": "build", "status": "PASS"}]}]}
]
}
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.
- 12d ago First seen · 96 lines · 62 tokens per session scan A 9b4ac341c83a
render-artifact is a skill published in the GitHub repository All-The-Vibes/ATV-PaperBoard (1 stars, last pushed 26d ago), licensed Apache-2.0. It adds 62 tokens to every session and 943 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 2026-08-31.
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