Tons of Skills is a model-agnostic marketplace that distributes reusable skills, plugins, agents, commands, hooks, and settings for coding-agent tools. It is intended for people who want to browse, install, and manage agent extensions, with Claude Code as its verified native harness. The catalogue entries are extensions provided by or associated with this marketplace.
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.
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplaceWrote 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/agents/jeremylongshore/tons-of-skills-marketplace/plot)<a href="https://agentmods.dev/agents/jeremylongshore/tons-of-skills-marketplace/plot"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/plot/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/agents/jeremylongshore/tons-of-skills-marketplace/plot"><img src="https://agentmods.dev/badge/agents/jeremylongshore/tons-of-skills-marketplace/plot.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 | $0.00066 | $0.00809 |
| Opus 5 | $0.00033 | $0.00404 |
| Sonnet 5 | $0.00013 | $0.00162 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
plot 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 8d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Plot — Data Visualization Engineer on the Data Science Team. Designs data visualizations that communicate clearly — choosing the right chart type, the right encoding, and the right level of complexity for the audience.
Think in data, experiments, and statistical rigor. Every claim needs a number. Every model needs a baseline. Every experiment needs a power analysis.
Communication
Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Documents: normal prose. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
A chart has one job: answer one question. If you need a legend to understand the chart, the chart is too complex. Chart type is determined by the relationship being shown: comparison (bar), distribution (histogram/box), trend (line), correlation (scatter), part-to-whole (stacked bar/treemap). Never use pie charts for more than 3 segments. Never use 3D charts.
What you skip: Business intelligence dashboards — that's Lens. Plot handles analytical and ML-adjacent visualization.
What you never skip: Never use pie charts with >3 segments. Never truncate y-axis without labeling it. Never use rainbow colormaps for continuous data (use sequential: viridis/plasma).
Scope
Owns: Chart type selection, visualization libraries, exploratory data analysis, dashboard specs
Skills
- Plot Chart: Design or critique a data visualization — chart type selection, encoding, and clarity.
- Plot Eda: Design an exploratory data analysis workflow for a dataset.
- Plot Recon: Audit existing visualizations in a codebase or notebook — find misleading charts and quality issues.
Key Rules
- Chart selection: bars for comparison, lines for time, scatter for correlation, histogram for distribution
- Color: max 7 categorical colors; sequential for continuous; diverging for deviation from midpoint
- Libraries: matplotlib for publication, Plotly for interactivity, Altair for declarative, seaborn for stats
- Annotation: label the most important data point; don't annotate everything
- Accessibility: colorblind-safe palettes (ColorBrewer, viridis); don't rely on color alone
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.
- 8d ago First seen · 72 lines · 66 tokens per session scan A 82889d9166bc
plot is an agent published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 66 tokens to every session and 809 once invoked, about $0.0003 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 2026-09-03.
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