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 agentmods add skills/spedas/spedas_agent_kit/wave-polarizationnpx skills add spedas/spedas_agent_kit --skill wave-polarizationgit 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/wave-polarization)<a href="https://agentmods.dev/skills/spedas/spedas_agent_kit/wave-polarization"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/wave-polarization.svg" alt="Measured on agentmods" 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 | $0.00093 | $0.01878 |
| Opus 5 | $0.00046 | $0.00939 |
| Sonnet 5 | $0.00019 | $0.00376 |
| Haiku 4.5 | $0.00009 | $0.00188 |
Grade A, and why
wave-polarization 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 6d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wave polarization analysis (twavpol)
The canonical IDL SPEDAS twavpol/wavpol analysis: from a 3-component B (or E)
waveform, decompose the fluctuations into polarization parameters vs time and
frequency. This is how you tell a field-aligned compressional wave from an
obliquely-propagating circularly-polarized whistler — the spectral power alone
(see solar-wind-turbulence-spectrum) can't.
When to use
- "Is this a whistler / EMIC / chorus wave? What's its wave-normal angle?"
- "Degree of polarization / ellipticity / helicity spectrogram for this interval."
- Any 3-component wave identification: parallel vs oblique, R- vs L-hand, planar vs random.
Tool chain (all existing)
load_data_source → browse_data_parameters → fetch_data_product (3-component B)
→ [optional generate_fac_matrix + apply to put B in field-aligned coords]
→ a small twavpol call → render_tplot, in a create_spedas_analysis_bundle.
MCP/default-surface boundary
twavpol is a PySPEDAS analysis backend, not an Agent Kit MCP tool
(external_runtime_route.not_an_mcp_tool: true). MCP-only clients should stop
after writing the fetched 3-component B artifact (and any optional FAC-rotation
artifacts) into an analysis bundle, then report that the polarization calculation
requires an external Python runtime with PySPEDAS and the Agent Kit [analysis]
extra. When that runtime is available, run the local script/notebook from the
bundle and record output paths in provenance/run.json; do not invent a
twavpol MCP call.
Backend (verified output contract)
pyspedas.analysis.twavpol.twavpol(tvarname, prefix=..., nopfft=..., steplength=..., bin_freq=...):
- Input: a single tplot variable holding an (N,3) vector time-series (the 3-component B).
- Returns:
1on success,0on failure (NOT the data — see the gotcha below). - Stores these tplot variables (retrieve with
get_data), each an (n_time, n_freq) spectrogram:{prefix}_powspec,{prefix}_degpol(degree of polarization 0–1),{prefix}_waveangle(wave-normal angle, deg),{prefix}_elliptict(ellipticity, −1..1),{prefix}_helict(helicity), and the per-component wave power variables{prefix}_pspec3_x,{prefix}_pspec3_y,{prefix}_pspec3_z.twavpoldoes not store a combined{prefix}_pspec3tplot variable in current PySPEDAS; combine the three component variables yourself only if a downstream artifact needs a single(n_time,n_freq,3)array.
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.
- 6d ago First seen · 84 lines · 93 tokens per session scan A 228d66059705
wave-polarization is a skill published in the GitHub repository spedas/spedas_agent_kit (3 stars, last pushed 1mo ago), licensed MIT. It adds 93 tokens to every session and 1,878 once invoked, about $0.0005 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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