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 saajunaid/caddis-plugin --skill word-cloudgit clone --depth 1 https://github.com/saajunaid/caddis-pluginWrote 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/saajunaid/caddis-plugin/word-cloud)<a href="https://agentmods.dev/skills/saajunaid/caddis-plugin/word-cloud"><img src="https://agentmods.dev/badge/skills/saajunaid/caddis-plugin/word-cloud/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/saajunaid/caddis-plugin/word-cloud"><img src="https://agentmods.dev/badge/skills/saajunaid/caddis-plugin/word-cloud.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 | $0.00041 | $0.03059 |
| Opus 5.5 | $0.00016 | $0.01224 |
| Sonnet 5.5 | $0.00008 | $0.00612 |
| Haiku 4.5 | $0.00004 | $0.00306 |
Grade A, and why
word-cloud 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 25d 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 — 340 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Word Cloud Skill
How to Use This Skill With Any AI Agent
This skill works with any AI coding assistant — Claude, GitHub Copilot (via Copilot Chat), Cursor, Windsurf, ChatGPT, Gemini Code Assist, etc.
To activate it, paste this prompt into your AI agent:
Read the file word-cloud-skill/SKILL.md and follow its instructions to generate a word cloud.
My input: [paste text OR file path]
My target stack: [react / html / python / streamlit]
For GitHub Copilot specifically:
- Open Copilot Chat in VS Code
- Drag the
SKILL.mdfile into the chat, or use#file:word-cloud-skill/SKILL.md - Then describe what you want
For Cursor:
- Add
word-cloud-skill/SKILL.mdto Cursor's context with@file - Or copy its contents into
.cursorrules
For any other agent:
- Simply paste the contents of
SKILL.mdas a system prompt or context block
Word Cloud Skill
Generates premium, visually stunning word clouds from any text source. The output is always a production-ready frontend component — not a placeholder or demo. Think editorial design meets data visualization: luxurious typography, intentional color, and satisfying motion.
Quick Decision Tree
Input source? → See §1 (Text Extraction)
Target stack? → See §2 (Stack Selection)
Want animation? → See §3 (Animation Modes)
Sentiment/POS? → See §4 (NLP Highlighting)
Shape/layout? → See §5 (Shape Masking)
Dark/light? → See §6 (Theming)
Agentic use? → See §7 (Agent Interface)
§1 · Text Extraction
Extract raw text first, then proceed to rendering. Use the appropriate method per file type.
Plain Text / HTML
Use directly — strip HTML tags with a regex or DOMParser if needed.
Read /mnt/skills/public/pdf-reading/SKILL.md for extraction strategy.
Preferred: pdfplumber (Python) or pdf-parse (Node).
DOCX
Read /mnt/skills/public/docx/SKILL.md.
Preferred: python-docx (Python) or mammoth (JS/browser).
XLSX / CSV
Read /mnt/skills/public/xlsx/SKILL.md.
Concatenate all cell text values from all sheets. For CSV: join all rows.
What ships with it
8 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.
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.
- 25d ago Changed · -23 tokens per session 4c5d2e06af8c
- 1mo ago First seen · 340 lines · 64 tokens per session scan A cefbcd868ea8
word-cloud is a skill published in the GitHub repository saajunaid/caddis-plugin (0 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 3,059 once invoked, about $0.0002 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 2026-09-03.
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