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 particle-distribution-recipesgit 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/particle-distribution-recipes)<a href="https://agentmods.dev/skills/spedas/spedas_agent_kit/particle-distribution-recipes"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/particle-distribution-recipes/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/particle-distribution-recipes"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/particle-distribution-recipes.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 | $0.00040 | $0.02209 |
| Opus 5 | $0.00020 | $0.01104 |
| Sonnet 5 | $0.00008 | $0.00442 |
| Haiku 4.5 | $0.00004 | $0.00221 |
Grade A, and why
particle-distribution-recipes 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 9d 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Particle distribution recipes
Use this skill when a researcher asks for MMS/ERG/THEMIS-style particle "distributions", 3D phase-space density, moments from distributions, energy / theta / phi / pitch-angle / gyro spectra, or velocity-space slices. This is an upstream route-scout and validation skill: it chooses a valid distribution product and artifact path, then hands off to the existing analysis tools and specialized skills.
It does not replace pitch-angle-distribution or
particle-velocity-slice. Those skills interpret already-built artifacts; this
skill decides whether the requested data are a real 3D distribution, how to
build/load the artifact, which side inputs are required, and which downstream
route should own the science product.
MCP/default-surface boundary
This skill adds no default MCP tool. Mission loaders and PySPEDAS/SPEDAS
particle helpers are external runtime vocabulary and must be marked with
external_runtime_route.not_an_mcp_tool: true unless a current Agent Kit server
actually exposes the action.
external_runtime_route:
not_an_mcp_tool: true
examples:
- pyspedas.projects.mms.particles.mms_part_getspec.mms_part_getspec
- pyspedas.projects.mms.particles.mms_part_products.mms_part_products
- pyspedas.projects.mms.particles.mms_part_slice2d.mms_part_slice2d
- pyspedas.projects.mms.fpi_tools.mms_pad_fpi.mms_pad_fpi
- pyspedas.projects.mms.fpi_tools.mms_load_fpi_calc_pad.mms_load_fpi_calc_pad
- pyspedas.projects.mms.fpi_tools.mms_get_fpi_dist.mms_get_fpi_dist
- pyspedas.projects.mms.hpca_tools.mms_get_hpca_dist.mms_get_hpca_dist
- pyspedas.particles.spd_slice2d.slice2d.slice2d
- pyspedas.particles.spd_part_products.spd_pgs_moments
- pyspedas.particles.moments_3d.moments_3d
- spedas_idl.spd_pgs_make_e_spec
- spedas_idl.spd_pgs_make_theta_spec
- spedas_idl.spd_pgs_make_phi_spec
- spedas_idl.thm_part_getspec
- spedas_idl.erg_pgs_moments
Do not invent MCP-prefixed PySPEDAS particle helpers, and do not present PySPEDAS functions as dedicated Agent Kit tools. The Agent Kit path is: plan a bounded mission/product query -> create an analysis bundle -> build or load a 3D distribution artifact -> compute moments/spectra or hand off to PAD/slice skills -> return artifact paths, compact metadata, and provenance.
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.
- 9d ago First seen · 160 lines · 40 tokens per session scan A 293d47f0f8ec
particle-distribution-recipes is a skill published in the GitHub repository spedas/spedas_agent_kit (3 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 2,209 once invoked, about $0.0002 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.
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