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 field-line-footpointgit 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/field-line-footpoint)<a href="https://agentmods.dev/skills/spedas/spedas_agent_kit/field-line-footpoint"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/field-line-footpoint/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/field-line-footpoint"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/field-line-footpoint.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 | $0.00086 | $0.01926 |
| Opus 5 | $0.00043 | $0.00963 |
| Sonnet 5 | $0.00017 | $0.00385 |
| Haiku 4.5 | $0.00009 | $0.00193 |
Grade A, and why
field-line-footpoint 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Field-line footpoint: trace a spacecraft to its ionospheric conjugate
A guided version of the pyspedas geopack field-line tracing crib — map a near-Earth
spacecraft position down a model field line to its ionospheric footpoint (for
ground/auroral conjunctions) or out to the magnetic equator (for L-shell / drift-shell
context). This is GUIDANCE around the existing evaluate_magnetic_field tool, which already
performs the trace; no new tool or code is added.
When to use
- "Where does this spacecraft map to on the ground / in the ionosphere?" (conjugate ground station, auroral oval, SuperDARN/THEMIS-GBO conjunction.)
- "Trace this field line to the magnetic equator / give me its L-shell apex."
- "Are these two spacecraft on the same field line / drift shell?" (footpoint or L comparison.)
Tool chain (all already exist)
get_ephemeris (or fetch_data_product for a position dataset) → transform_coordinates
(to GSM) → evaluate_magnetic_field(trace="ionosphere" | "equator", model=...)
→ read footpoints from the output .npz → (render_tplot for the per-sample series),
all inside a create_spedas_analysis_bundle. For McIlwain L specifically,
calculate_lshell is the equatorial-trace shortcut.
Backend (VERIFIED contract)
evaluate_magnetic_field wraps pyspedas geopack tigrf/tt89/tt96/tt01/tts04 (field) and
ttrace2endpoint (tracing). Key facts that drive this skill:
- Input is a positions artifact:
.npzwithpositions= N×3 in GSM, kilometers (and optionaltimes); or.npy; or CSV/JSON withposition_cols/time_col. Positions are not auto-transformed — you must hand it GSM. trace∈{none, ionosphere, equator}, mapped tottrace2endpointendpoints."ionosphere"traces along the field line to the ionospheric foot;"equator"traces to the magnetic equator.- Output is
output_fileas.npz: per-sample B (nT) for every position, plus footpoints when tracing, plus an L series forequatortraces. The tool returns only the model,field_strength_nTmin/max/mean, paths, and (for equator) anlshell_summary— never the raw arrays. Read the.npzyourself to get coordinates. model:igrf(default) is fast and parameter-free. Distorted external models (t89,t96,t01,ts04) require explicitparameters(geomagnetic / solar-wind drivers — e.g. Dst, Pdyn, By/Bz, G/W indices as the model demands); there is no hidden network I/O, so missing/garbage parameters give a silently wrong field, not an error.calculate_lshellis the same machinery specialized to an equator trace: equatorial foot radius in Re = McIlwain L; returns{min_L, max_L, mean_L}+ paths, optional ionosphericfootprint=True.
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 · 61 lines · 86 tokens per session scan A e50e20ea6d65
field-line-footpoint is a skill published in the GitHub repository spedas/spedas_agent_kit (3 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 1,926 once invoked, about $0.0004 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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