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 spedas/spedas_agent_kit --skill pytplot-plotting-optionsgit clone --depth 1 https://github.com/spedas/spedas_agent_kitWrote 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/spedas/spedas_agent_kit/pytplot-plotting-options)<a href="https://agentmods.dev/skills/spedas/spedas_agent_kit/pytplot-plotting-options"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/pytplot-plotting-options/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/spedas/spedas_agent_kit/pytplot-plotting-options"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/pytplot-plotting-options.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 | $0.00049 | $0.02016 |
| Opus 5.5 | $0.00020 | $0.00806 |
| Sonnet 5.5 | $0.00010 | $0.00403 |
| Haiku 4.5 | $0.00005 | $0.00202 |
Grade A, and why
pytplot-plotting-options 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PyTplot plotting options
Use this skill when a request mentions PyTplot, tplot, IDL SPEDAS plot
options, spectrogram styling, y/z limits, log axes, labels, legends, event bars,
plot highlights, saved PNG/SVG/PDF figures, or "make this SPEDAS plot look like
...". It complements tplot-data-lifecycle: first make variable state and
metadata explicit, then use this skill to decide the plot option manifest and
artifact output.
MCP/default-surface boundary
This skill adds no MCP tool. PySPEDAS/PyTplot plotting calls are source evidence
or external runtime routes and must be marked with the structured marker
external_runtime_route.not_an_mcp_tool: true unless a current Agent Kit tool
explicitly exposes the action.
external_runtime_route:
not_an_mcp_tool: true
examples:
- pyspedas.options
- pyspedas.tplot_options
- pyspedas.tplot
- pyspedas.ylim
- pyspedas.zlim
- pyspedas.xlim
- pyspedas.tlimit
- pyspedas.timebar
- pyspedas.databar
- pyspedas.tplot_tools.MPLPlotter.highlight
- pyspedas.tplot_tools.MPLPlotter.annotate
Do not tell an MCP-only client to call invented MCP-prefixed PySPEDAS
option or plotting tools, and do not present pyspedas.tplot as a dedicated
Agent Kit tool. The Agent Kit path is: choose the variables and plot semantics
-> create/update the run bundle -> let the backend/[analysis] route such as
render_tplot (when enabled) or a runtime PySPEDAS script write figure
artifacts -> return paths, hashes, plot_options.json, and
provenance/run.json entries.
Recipe model
- Start from variable metadata. Load
tplot-data-lifecyclefirst if variable names, dimensions, units, coordinate frames, cadence, support-data flags, or fill/interpolation status are unclear. Do not paste arrays. - Choose plot family. A scalar/vector time series is a line/panel plot; an energy/frequency/pitch-angle product is usually a spectrogram; a pseudo-var panel may combine multiple variables. Record this decision in a plot manifest.
- Separate global from per-variable options. Use global options for the figure/window/time context; use per-variable options for panel semantics.
- Save an artifact, not an interactive window. In headless Agent Kit runs,
prefer saved files (
save_png,save_svg,save_pdf, orsave_jpeg) withdisplay=False. Return the file path and a compact option summary. - Record interpretation-changing choices. Log axes, clipping versus display
limits, z ranges, color maps, event bars, annotations, and any plot-time data
gap handling belong in
provenance/run.jsonand a sidecar such asplot_options.json.
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 · 136 lines · 49 tokens per session scan A 8a0917f17e95
pytplot-plotting-options is a skill published in the GitHub repository spedas/spedas_agent_kit (3 stars, last pushed 2mo ago), licensed MIT. It adds 49 tokens to every session and 2,016 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 2026-08-31.
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