New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Antv T8 Ntv

by antvis in antvis/chart-visualization-skills

Generate structured narrative text visualizations from data using T8 Syntax.

MITAuto-check passedData & Analytics

Install Antv T8 Ntv

skills CLI
$ npx skills add antvis/chart-visualization-skills --skill antv-t8-ntv -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install antvis/chart-visualization-skills antv-t8-ntv --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/antvis/chart-visualization-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/antv-t8-ntv .claude/skills/antv-t8-ntv && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
antv-t8-ntv
GitHub stars
506
Token cost
~4.5k tokens
SKILL.md length
1,317 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Generate structured narrative text visualizations from data using T8 Syntax.

  • Works in 4 steps: Understand the Requirements → Generate T8 Syntax Content → Generate Frontend Code → …
  • Users want to create data interpretation reports
  • SKILL.md covers What is T8, Workflow, T8 Syntax Specification and Data Requirements, plus 5 more sections
  • Calls npm and yarn; reaches unpkg.com

What it does

Antv T8 Ntv is an agent skill from antvis/chart-visualization-skills. Generate structured narrative text visualizations from data using T8 Syntax. Use when users want to create data interpretation reports, summaries, or structured articles with semantic entity annotations. T8 is designed for unstructured data visualization where T stands for Text and 8 represents a byte of 8 bits, symbolizing deep insights beneath the text.

Its SKILL.md is about 4.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Data visualization. The repository describes itself as: ⛏️ Turning data into a visual language for better thinking with Skills. The licence is MIT.

When your agent uses it

  • Users want to create data interpretation reports
  • Structured articles with semantic entity annotations

Example prompts

  • “/antv-t8-ntv”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Understand the Requirements
  2. Generate T8 Syntax Content
  3. Generate Frontend Code
  4. Validate Output

What it can do on your machine

Read from SKILL.md and the folder at commit a105fa1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm
    • yarn

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • unpkg.com

    Also links to:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Antv T8 Ntv loads about 4.5k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 1,317 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~4.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from antvis/chart-visualization-skills at commit a105fa1, republished under its MIT licence (© antvis). 1,317 words, ~4,543 tokens.

Download SKILL.mdSave it as .claude/skills/antv-t8-ntv/SKILL.md (or your agent's skills folder).
name
antv-t8-ntv
description
Generate structured narrative text visualizations from data using T8 Syntax. Use when users want to create data interpretation reports, summaries, or structured articles with semantic entity annotations. T8 is designed for unstructured data visualization where T stands for Text and 8 represents a byte of 8 bits, symbolizing deep insights beneath the text.

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.

Document Structure
Headings (6 levels)

Use standard Markdown heading syntax:

# Level 1 Heading (Main Title)
## Level 2 Heading (Section)
### Level 3 Heading (Subsection)
#### Level 4 Heading
##### Level 5 Heading
###### Level 6 Heading

Rules:

  • Each heading must be on its own line
  • Add one space after the # symbols
  • Headings create visual hierarchy in the rendered output
Paragraphs

Regular text paragraphs are separated by blank lines:

This is the first paragraph with some content.

This is the second paragraph, separated by a blank line.

Rules:

  • Paragraphs can span multiple lines
  • Use blank lines to separate distinct paragraphs
  • Text within a paragraph flows naturally
Lists

T8 Syntax supports both unordered and ordered lists.

Unordered Lists:

- First item
- Second item
- Third item

Ordered Lists:

1. First step
2. Second step
3. Third step

Rules:

  • Each list item must be on its own line
  • Add one space after the bullet marker (-, *) or number
  • Lists can contain entities and text formatting
Text Formatting

T8 Syntax supports inline text formatting using Markdown syntax:

Bold Text: This is **bold text** that stands out.

Italic Text: This is *italic text* for emphasis.

Underline Text: This is __underlined text__ for importance.

Links: Visit [our website](https://example.com) for more information.

Rules:

  • Formatting markers must be balanced (opening and closing)
  • Formatting can be combined with entities
  • Links use [text](URL) syntax where URL starts with http://, https://, or /
Entity Annotation Syntax

The core feature of T8 Syntax is entity annotation - marking specific data points with semantic meaning and metadata.

Basic Entity Syntax
[displayText](entityType)
  • displayText: The text shown to readers
  • entityType: The semantic type of this entity

Example:

The [sales revenue](metric_name) reached [¥1.5 million](metric_value) this quarter.
Entity with Metadata
[displayText](entityType, key1=value1, key2=value2, key3="string value")

Metadata Rules:

  • Separate multiple metadata fields with commas
  • Numbers and booleans: write directly (e.g., origin=1500000, active=true)
  • Strings: wrap in double quotes (e.g., unit="元", region="Asia")

Example:

Revenue grew by [15.3%](ratio_value, origin=0.153, assessment="positive") compared to last year.
Entity Types Reference

Use these entity types to annotate different kinds of data:

Entity TypeDescriptionWhen to UseExamples
metric_nameName of a metric or KPIWhen mentioning what you're measuring"revenue", "user count", "market share"
metric_valuePrimary metric valueThe main number/value being reported"¥1.5 million", "50,000 users", "250 units"
other_metric_valueSecondary or supporting metric valueAdditional metrics that provide context"average order value: $120"
delta_valueAbsolute change/differenceWhen showing numeric change between periods"+1,200 units", "-$50K", "increased by 500"
ratio_valuePercentage change/rateWhen showing percentage change"+15.3%", "-5.2%", "grew 23%"
contribute_ratioContribution percentageWhen showing what % something contributes"accounts for 45%", "represents 30% of total"
trend_descTrend descriptionDescribing direction/pattern of change"steadily rising", "declining trend", "stable"
dim_valueDimensional value/categoryGeographic, categorical, or segmentation data"North America", "Enterprise segment", "Q3"
time_descTime period or timestampWhen specifying when something occurred"Q3 2024", "January-March", "fiscal year 2023"
proportionProportion or ratioWhen expressing parts of a whole"3 out of 5", "60% of customers"
rankRanking or positionWhen indicating order or position in a list"ranked 1st", "top 3", "5th place"
differenceComparative differenceWhen highlighting difference between two items"difference of $50K", "gap of 200 units"
anomalyUnusual or unexpected valueWhen pointing out outliers or anomalies"unusual spike", "unexpected drop"
associationRelationship or correlationWhen describing connections between metrics"strongly correlated", "linked to", "related"
distributionData distribution patternWhen describing how data is spread"evenly distributed", "concentrated in", "spread across"
seasonalitySeasonal pattern or trendWhen describing recurring seasonal patterns"seasonal peak", "holiday period", "Q4 surge"
Common Metadata Fields

Add these optional fields to provide richer data context:

Show full SKILL.md (524 more words)Show less
origin (number)

The raw numerical value behind the displayed text.

Examples:

  • [¥1.5M](metric_value, origin=1500000)
  • [23.7%](ratio_value, origin=0.237)
  • [5.2K users](metric_value, origin=5200)
  • [3 out of 4](proportion, origin=0.75)

Why use it: Enables data visualization, sorting, and calculations

assessment (string)

Evaluates whether a change is positive, negative, or neutral.

Valid values: "positive", "negative", "equal", "neutral"

Examples:

  • [increased 15%](ratio_value, assessment="positive")
  • [dropped 8%](ratio_value, assessment="negative")
  • [remained flat](trend_desc, assessment="equal")

Why use it: Enables visual indicators (colors, icons) for good/bad trends

unit (string)

The unit of measurement for the value.

Examples:

  • [¥1,500,000](metric_value, unit="元", origin=1500000)
  • [150](metric_value, unit="units")
detail (any)

Additional context or breakdown data for chart rendering. Required for certain entity types.

Required for these entity types:

  • rank: Array of numbers representing ranking data
    • Example: [top performer](rank, detail=[5, 8, 12, 15, 20])
  • difference: Array of numbers showing comparative values
    • Example: [gap narrowing](difference, detail=[100, 80, 60, 40])
  • anomaly: Array of numbers highlighting outliers
    • Example: [unusual spike](anomaly, detail=[10, 12, 11, 45, 13])
  • association: Array of {x, y} objects for correlation data
    • Example: [strong correlation](association, detail=[{"x":1,"y":2},{"x":2,"y":4},{"x":3,"y":6}])
  • distribution: Array of numbers showing data spread
    • Example: [uneven distribution](distribution, detail=[5, 15, 45, 25, 10])
  • seasonality: Object with data array and optional range
    • Example: [Q4 peak](seasonality, detail={"data":[10,12,15,30],"range":[0,40]})

Optional for other types:

  • [steady growth](trend_desc, detail=[100, 120, 145, 180, 210])

Data Requirements

Critical: All data must be from publicly authentic sources:

  • Official announcements/financial reports
  • Authoritative media (Reuters, Bloomberg, TechCrunch, etc.)
  • Industry research institutions (IDC, Canalys, Counterpoint Research, etc.)
  • Never use fictional, AI-guessed, or simulated data
  • Use specific numbers (e.g., "146 million units", "7058 units"), not vague approximations

Complete T8 Syntax Example

# 2024 Smartphone Market Analysis

## Market Overview

Global [smartphone shipments](metric_name) reached [1.2 billion units](metric_value, origin=1200000000) in [2024](time_desc), showing a [modest decline of 2.1%](ratio_value, origin=-0.021, assessment="negative") year-over-year.

The **premium segment** (devices over $800) showed *remarkable* [resilience](trend_desc, assessment="positive"), growing by [5.8%](ratio_value, origin=0.058, assessment="positive"). [Average selling price](other_metric_value) was [$420](metric_value, origin=420, unit="USD").

## Key Findings

1. [Asia-Pacific](dim_value) remains the __largest market__
2. [Premium devices](dim_value) showed **strong growth**
3. Budget segment faced *headwinds*

## Regional Breakdown

### Asia-Pacific

[Asia-Pacific](dim_value) remains the largest market with [680 million units](metric_value, origin=680000000) shipped, though this represents a [decline of 180 million units](delta_value, origin=-180000000, assessment="negative") from the previous year.

Key markets:
- [China](dim_value): [320M units](metric_value, origin=320000000) - down [8.5%](ratio_value, origin=-0.085, assessment="negative"), [ranked 1st](rank, detail=[320, 180, 90, 65, 45]) globally, accounting for [47%](contribute_ratio, origin=0.47, assessment="positive") of regional sales
- [India](dim_value): [180M units](metric_value, origin=180000000) - up [12.3%](ratio_value, origin=0.123, assessment="positive"), [ranked 2nd](rank, detail=[320, 180, 90, 65, 45])
- [Southeast Asia](dim_value): [180M units](metric_value, origin=180000000) - [stable](trend_desc, assessment="equal")

For detailed methodology, visit [our research page](https://example.com/methodology).

Using T8 in HTML, React, and Vue

Using in HTML (via CDN)
html
<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>T8 Narrative Text</title>
</head>
<body>
  <div id="container"></div>

  <!-- Import T8 from unpkg CDN -->
  <script src="https://unpkg.com/@antv/t8/dist/t8.min.js"></script>
  
  <script>
    // T8 is available as a global variable
    const { Text } = window.T8;

    // Initialize T8 instance
    const text = new Text(document.getElementById('container'));

    // Render narrative text using T8 Syntax
    const narrativeText = `
# Sales Report

This quarter, [bookings](metric_name) are higher than usual. They are [¥348k](metric_value, origin=348.12).

[Bookings](metric_name) are up [¥180.3k](delta_value, assessment="positive") relative to the same time last quarter.
    `;

    text.theme('light').render(narrativeText);
  </script>
</body>
</html>

Installation:

bash
npm install @antv/t8
# or
yarn add @antv/t8
Using in React
tsx
import { Text } from '@antv/t8';
import { useEffect, useRef } from 'react';

function T8Component() {
  const containerRef = useRef<HTMLDivElement>(null);

  useEffect(() => {
    if (!containerRef.current) return;

    // Initialize T8 instance
    const text = new Text(containerRef.current);

    // Render narrative text using T8 Syntax
    const narrativeText = `
# Sales Report

This quarter, [bookings](metric_name) are higher than usual. They are [¥348k](metric_value, origin=348.12).

[Bookings](metric_name) are up [¥180.3k](delta_value, assessment="positive") relative to the same time last quarter.
    `;

    text.theme('light').render(narrativeText);

    // Cleanup on unmount
    return () => {
      text.unmount();
    };
  }, []);

  return <div ref={containerRef} />;
}

export default T8Component;
Using in Vue 3
vue
<template>
  <div ref="containerRef"></div>
</template>

<script setup lang="ts">
import { Text } from '@antv/t8';
import { ref, onMounted, onBeforeUnmount } from 'vue';

const containerRef = ref<HTMLDivElement>();
let textInstance: Text | null = null;

onMounted(() => {
  if (!containerRef.value) return;

  // Initialize T8 instance
  textInstance = new Text(containerRef.value);

  // Render narrative text using T8 Syntax
  const narrativeText = `
# Sales Report

This quarter, [bookings](metric_name) are higher than usual. They are [¥348k](metric_value, origin=348.12).

[Bookings](metric_name) are up [¥180.3k](delta_value, assessment="positive") relative to the same time last quarter.
  `;

  textInstance.theme('light').render(narrativeText);
});

onBeforeUnmount(() => {
  if (textInstance) {
    textInstance.unmount();
  }
});
</script>
Using in Vue 2
vue
<template>
  <div ref="container"></div>
</template>

<script>
import { Text } from '@antv/t8';

export default {
  name: 'T8Component',
  data() {
    return {
      textInstance: null,
    };
  },
  mounted() {
    // Initialize T8 instance
    this.textInstance = new Text(this.$refs.container);

    // Render narrative text using T8 Syntax
    const narrativeText = `
# Sales Report

This quarter, [bookings](metric_name) are higher than usual. They are [¥348k](metric_value, origin=348.12).

[Bookings](metric_name) are up [¥180.3k](delta_value, assessment="positive") relative to the same time last quarter.
    `;

    this.textInstance.theme('light').render(narrativeText);
  },
  beforeDestroy() {
    if (this.textInstance) {
      this.textInstance.unmount();
    }
  },
};
</script>

Writing Guidelines and Best Practices

Content Requirements
  1. Minimum Length: No less than 800 words (adjust based on data complexity)
  2. Structure: Clear hierarchy with logical flow between sections
  3. Analysis: Don't just list numbers - explain their significance and context
  4. Tone: Natural, fluent, objective, and professional
  5. Entity Usage: Annotate ALL meaningful data points - metrics, values, trends, times, changes, percentages
Entity Annotation Best Practices
  1. Be Comprehensive: Mark all quantitative data, not just major figures
  2. Use Appropriate Types: Choose the entity type that best describes the semantic meaning
  3. Add Metadata: Include origin, assessment, and other relevant fields when applicable
  4. Natural Flow: Entities should blend seamlessly into readable prose
What to Annotate

✅ DO annotate:

  • All numeric values (revenue, counts, measurements)
  • All percentages (changes, contributions, proportions)
  • Metric names and KPIs
  • Time periods
  • Geographic regions and categories
  • Trend descriptions
  • Comparisons and changes

❌ DON'T annotate:

  • Generic text without specific data meaning
  • Connecting phrases and transitions
  • Context that doesn't represent measurable concepts

Output Format

When generating T8 Syntax content for the user:

  1. Output the T8 Syntax content directly without wrapping in code blocks
  2. Provide the frontend code (HTML/React/Vue) based on user preference
  3. Ensure all entities are properly annotated with appropriate metadata
  4. Verify that content meets minimum length and quality requirements

The rendered output provides:

  • Rich semantic markup for data entities
  • Interactive entity highlighting
  • Clear visual hierarchy
  • Professional report-style formatting
  • Responsive design for all devices

© antvis, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/antv-t8-ntv of antvis/chart-visualization-skills.

Open the folder on GitHubat commit a105fa1

Compare with similar skills

Antv T8 Ntv next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Antv T8 Ntv compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Antv T8 Ntv this skillantvis/chart-visualization-skills506—~4.5kAutomated safety check: PassMIT
MatplotlibzLanqing/codex-claude-academic-skills4.7k17 repos~2.9kAutomated safety check: PassMIT
Chart Visualizationbytedance/deer-flow84k1 repos~840Automated safety check: PassMIT
Scientific Visualizationmims-harvard/OptimusKG14719 repos~6.3kAutomated safety check: PassMIT
SeabornzLanqing/codex-claude-academic-skills4.7k15 repos~4.9kAutomated safety check: PassBSD-3-Clause
Plot From DataTrae1ounG/paper-plot-skills8721 repos~583Automated safety check: PassNone

Similar skills

  • Matplotlib

    zLanqing/codex-claude-academic-skills

    Low-level plotting library for full customization. An agent skill from zLanqing/codex-claude-academic-skills.

    4.7k GitHub starsUsed in 17 repos~2.9k tokens
    Data & AnalyticsAuto-check passed

  • Chart Visualization

    bytedance/deer-flow

    Picks a suitable chart type from 26 options for your data, maps the data to that chart's parameters and generates a chart image through a JavaScript script.

    84k GitHub starsUsed in 1 repo~840 tokens
    Data & AnalyticsAuto-check passed

  • Scientific Visualization

    mims-harvard/OptimusKG

    Create publication figures with matplotlib/seaborn/plotly. An agent skill from mims-harvard/OptimusKG.

    147 GitHub starsUsed in 19 repos~6.3k tokens
    Data & AnalyticsAuto-check passed

  • Seaborn

    zLanqing/codex-claude-academic-skills

    Statistical visualization with pandas integration. An agent skill from zLanqing/codex-claude-academic-skills.

    4.7k GitHub starsUsed in 15 repos~4.9k tokens
    Data & AnalyticsAuto-check passed

  • Plot From Data

    Trae1ounG/paper-plot-skills

    Generate publication-quality matplotlib figures by selecting a pre-built paper style and substituting user data.

    872 GitHub starsUsed in 1 repo~583 tokens
    Data & AnalyticsAuto-check passed

  • Scientific Figure Making

    ChenLiu-1996/figures4papers

    Covers publication-ready matplotlib figures for academic papers, slides, and reports—bars, trends, scatter, heatmaps, and multi-panel layouts—with this…

    8.3k GitHub stars~557 tokensUpdated yesterday
    Data & AnalyticsAuto-check passed

More from antvis/chart-visualization-skills

All 9 skills in this repo

  • Antv G2 Chart

    antvis/chart-visualization-skills

    A skill your agent uses whenever the user wants to create, customize, or troubleshoot G2 v5 chart visualizations.

    506 GitHub stars~2.5k tokensUpdated 19 days ago
    Auto-check passed

  • Antv G6 Graph

    antvis/chart-visualization-skills

    A skill your agent uses whenever the user wants to create, customize, or troubleshoot G6 v5 graph/network visualizations.

    506 GitHub stars~1.8k tokensUpdated 19 days ago
    Auto-check passed

  • Antv Infographic

    antvis/chart-visualization-skills

    Create beautiful infographics based on given text content. An agent skill from antvis/chart-visualization-skills.

    506 GitHub stars~3k tokensUpdated 19 days ago
    Auto-check passed

  • Antv X6 Editor

    antvis/chart-visualization-skills

    A skill your agent uses whenever the user wants to create, customize, or troubleshoot X6 v3 graph editor diagrams.

    506 GitHub stars~2.9k tokensUpdated 19 days ago
    Auto-check passed

  • Antv Gpt Vis

    antvis/chart-visualization-skills

    Recommend and generate appropriate data visualization charts using the GPT-Vis library.

    506 GitHub stars~3.7k tokensUpdated 19 days ago
    Auto-check passed

  • Gpt Vis

    antvis/chart-visualization-skills

    推荐并生成合适的数据可视化图表，使用 GPT-Vis 库。支持两种输出模式：（1）语法模式——生成 Syntax 或 JSON 配置；（2）代码模式——生成完整的运行代码。支持 26 种图表类型。

    506 GitHub stars~2.5k tokensUpdated 19 days ago
    Auto-check passed

Categories

Questions about Antv T8 Ntv

What does Antv T8 Ntv do?

Generate structured narrative text visualizations from data using T8 Syntax. Antv T8 Ntv is an agent skill from antvis/chart-visualization-skills. Generate structured narrative text visualizations from data using T8 Syntax.

When should I use Antv T8 Ntv?

Antv T8 Ntv fits situations like: users want to create data interpretation reports; structured articles with semantic entity annotations.

How do I install Antv T8 Ntv in Claude Code?

Run `npx skills add antvis/chart-visualization-skills --skill antv-t8-ntv -a claude-code`. Or copy the skill folder (skills/antv-t8-ntv in antvis/chart-visualization-skills) into .claude/skills/antv-t8-ntv in your project. Claude Code loads it when a task matches its description.

How do I install Antv T8 Ntv in Codex?

Run `npx skills add antvis/chart-visualization-skills --skill antv-t8-ntv -a codex`. Or copy the skill folder (skills/antv-t8-ntv in antvis/chart-visualization-skills) into .agents/skills/antv-t8-ntv in your project. Codex loads it when a task matches its description.

Can I use Antv T8 Ntv in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add antvis/chart-visualization-skills --skill antv-t8-ntv -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/antv-t8-ntv, .gemini/skills/antv-t8-ntv, .github/skills/antv-t8-ntv and .opencode/skills/antv-t8-ntv in your project.

What does Antv T8 Ntv need to run?

Going by SKILL.md and its folder, Antv T8 Ntv needs the command-line tools its instructions call (npm and yarn).

Does Antv T8 Ntv access the network?

SKILL.md names 2 domains. In commands or code: unpkg.com; the agent is likely to contact it when it follows the instructions. As links in the text: github.com. This is read from the text; nothing was executed.

Is Antv T8 Ntv safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Antv T8 Ntv use?

Antv T8 Ntv is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Antv T8 Ntv use?

About 4.5k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Antv T8 Ntv?

Skills that share tags, products or a category with Antv T8 Ntv: Matplotlib (zLanqing/codex-claude-academic-skills, 4.7k stars), Chart Visualization (bytedance/deer-flow, 84k stars), Scientific Visualization (mims-harvard/OptimusKG, 147 stars) and Seaborn (zLanqing/codex-claude-academic-skills, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Antv T8 Ntv?

antvis (a GitHub organization) maintains it in antvis/chart-visualization-skills, which has 506 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 22, 2026.

Source: antvis/chart-visualization-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.