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 antvis/chart-visualization-skills --skill antv-t8-ntvgit clone --depth 1 https://github.com/antvis/chart-visualization-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/antvis/chart-visualization-skills/antv-t8-ntv)<a href="https://agentmods.dev/skills/antvis/chart-visualization-skills/antv-t8-ntv"><img src="https://agentmods.dev/badge/skills/antvis/chart-visualization-skills/antv-t8-ntv/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/antvis/chart-visualization-skills/antv-t8-ntv"><img src="https://agentmods.dev/badge/skills/antvis/chart-visualization-skills/antv-t8-ntv.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 | $0.00074 | $0.04340 |
| Opus 5.5 | $0.00030 | $0.01736 |
| Sonnet 5.5 | $0.00015 | $0.00868 |
| Haiku 4.5 | $0.00007 | $0.00434 |
Grade A, and why
antv-t8-ntv 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 23d 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 — 520 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Narrative Text Visualization Skill
This skill provides a workflow for transforming data into structured narrative text visualizations using T8 Syntax - a declarative Markdown-like language for creating data narratives with semantic entity annotations.
What is T8
T8 is a text visualization solution under the AntV technology stack designed specifically for insight-based narrative text display. Instead of manually constructing DOM elements, you write simple, human-readable syntax that describes your data narrative.
Key Features:
- LLM-Friendly: The syntax is intuitive and can be easily generated by AI models
- Declarative & Readable: Write what you want, not how to build it
- Framework Agnostic: Works with React, Vue, or vanilla JavaScript
- Standardized Styling: Professional appearance by default
- Built-in Data Visualizations: Mini charts (pie, line) are native to the syntax
- Lightweight: Less than 20KB before gzip
Workflow
To generate narrative text visualizations, follow these steps:
1. Understand the Requirements
Analyze the user's request to determine:
- The topic or data to be analyzed
- The type of narrative needed (report, summary, article)
- The key insights to highlight
- Any specific data sources or metrics
2. Generate T8 Syntax Content
Create narrative text using T8 Syntax following the specification below. The content must include:
- Proper document structure (headings, paragraphs, lists)
- Entity annotations for all meaningful data points
- Appropriate metadata for entities (origin, assessment, etc.)
3. Generate Frontend Code
Create HTML, React, or Vue code to render the T8 content based on user's preferred framework.
4. Validate Output
Ensure:
- All data is from authentic sources
- Minimum content length (800 words or equivalent)
- Proper entity annotations throughout
- Clear structure and logical flow
T8 Syntax Specification
T8 Syntax is a Markdown-like language for creating narrative text with semantic entity annotations. It makes data analysis reports more expressive and visually appealing.
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.
- 23d ago First seen · 520 lines · 74 tokens per session scan A a089c390f399
antv-t8-ntv is a skill published in the GitHub repository antvis/chart-visualization-skills (509 stars, last pushed 24d ago), licensed MIT. It adds 74 tokens to every session and 4,340 once invoked, about $0.0003 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 2026-09-23.
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