visualize

A data-visualisation tool that creates charts and plots, including line, bar, pie, heatmap, scatter, and histogram charts.

In plain words
What is it for?
It is for generating charts and plots from data.
Why use it?
It turns data into visual formats that can make patterns and comparisons easier to inspect.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/openanalystinc/10x-analyst/visualize
Any agent
npx skills add OpenAnalystInc/10x-analyst --skill visualize
Clone the repo
git clone --depth 1 https://github.com/OpenAnalystInc/10x-analyst

Made for: Claude Code, Codex.

Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 889 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.00889
Opus 5 $0.00011 $0.00445
Sonnet 5 $0.00004 $0.00178
Haiku 4.5 $0.00002 $0.00089

Measured 2d ago against content hash 9bb173992dbb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

visualize 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 2d 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.

skills/visualize/SKILL.md · 106 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

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.

  1. 2d ago First seen · 106 lines · 22 tokens per session scan A 9bb173992dbb

Subscribe to this mod's changes

visualize is a skill published in the GitHub repository OpenAnalystInc/10x-analyst (4 stars, last pushed 5mo ago), with no licence file. It adds 22 tokens to every session and 889 once invoked, about $0.0001 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.

Related

Other skills, from other repositories

improving-frontend-coverage

Runs frontend unit tests with coverage, analyzes coverage reports, and implements meaningful tests to increase coverage by 0.2%. Use when you want to systematically improve frontend test coverage with high-value test cases.

streamlit/streamlit · 48 tokens

developing-with-streamlit

Use for ALL Streamlit tasks: creating, editing, debugging, beautifying, styling, theming, optimizing, or deploying Streamlit apps. Also custom components, st.components.v2, HTML/JS/CSS work. Discovers and loads version-matched reference docs from the user's installed Streamlit (>=1.57). Triggers: streamlit, st.…

streamlit/streamlit · 128 tokens

connector-review

Review an OpenMetadata connector against golden standards. Runs multi-agent analysis covering architecture, code quality, type safety, testing, and performance. When a PR number is given, automatically posts the quality summary to the PR description and a detailed review as a PR comment.

open-metadata/OpenMetadata · 55 tokens

pr-checklist

Use when opening or finalizing a GitHub PR for OpenMetadata. Walks through the repo PR template — linked issue, high-level design (for big PRs), unit/integration/Playwright tests + coverage, UI screen recording, and manual test steps — then drafts a fully-filled PR body and (optionally) creates the PR.

open-metadata/OpenMetadata · 73 tokens

connector-standards

Load all OpenMetadata connector development standards into context. Use before building or reviewing connectors to ensure consistent patterns.

open-metadata/OpenMetadata · 26 tokens

sn-da-large-file-analysis

万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl readonly 流式读取(iterrows 支持 10 万行以上)、Parquet 转换加速、内存优化、分块处理和大文件写入模式。遇到以下任一情况就主动使用本 skill:①数据行数 ≥ 10k(由 sn-da-excel-workflow 的行数评估步骤触发);②用户出现触发词:大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing;③直接使用…

OpenSenseNova/SenseNova-Skills · 218 tokens