Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/fergupa/claude_pluginsnpx agentmods add commands/fergupa/claude_plugins/create-vizWrote 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/commands/fergupa/claude_plugins/create-viz)<a href="https://agentmods.dev/commands/fergupa/claude_plugins/create-viz"><img src="https://agentmods.dev/badge/commands/fergupa/claude_plugins/create-viz/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/commands/fergupa/claude_plugins/create-viz"><img src="https://agentmods.dev/badge/commands/fergupa/claude_plugins/create-viz.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 | $0.00007 | $0.01153 |
| Opus 5.5 | $0.00003 | $0.00461 |
| Sonnet 5.5 | $0.00001 | $0.00231 |
| Haiku 4.5 | $0.00001 | $0.00115 |
Grade A, and why
create-viz 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 1mo 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/create-viz - Create Visualizations
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Create publication-quality data visualizations using Python. Generates charts from data with best practices for clarity, accuracy, and design.
Usage
/create-viz <data source> [chart type] [additional instructions]
Workflow
1. Understand the Request
Determine:
- Data source: Query results, pasted data, CSV/Excel file, or data to be queried
- Chart type: Explicitly requested or needs to be recommended
- Purpose: Exploration, presentation, report, dashboard component
- Audience: Technical team, executives, external stakeholders
2. Get the Data
If data warehouse is connected and data needs querying:
- Write and execute the query
- Load results into a pandas DataFrame
If data is pasted or uploaded:
- Parse the data into a pandas DataFrame
- Clean and prepare as needed (type conversions, null handling)
If data is from a previous analysis in the conversation:
- Reference the existing data
3. Select Chart Type
If the user didn't specify a chart type, recommend one based on the data and question:
| Data Relationship | Recommended Chart |
|---|---|
| Trend over time | Line chart |
| Comparison across categories | Bar chart (horizontal if many categories) |
| Part-to-whole composition | Stacked bar or area chart (avoid pie charts unless <6 categories) |
| Distribution of values | Histogram or box plot |
| Correlation between two variables | Scatter plot |
| Two-variable comparison over time | Dual-axis line or grouped bar |
| Geographic data | Choropleth map |
| Ranking | Horizontal bar chart |
| Flow or process | Sankey diagram |
| Matrix of relationships | Heatmap |
Explain the recommendation briefly if the user didn't specify.
4. Generate the Visualization
Write Python code using one of these libraries based on the need:
- matplotlib + seaborn: Best for static, publication-quality charts. Default choice.
- plotly: Best for interactive charts or when the user requests interactivity.
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.
- 1mo ago First seen · 154 lines · 7 tokens per session scan A 0c50831f19e5
create-viz is a command published in the GitHub repository fergupa/claude_plugins (2 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 7 tokens to every session and 1,153 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.