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 spedas-workflowgit 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/spedas-workflow)<a href="https://agentmods.dev/skills/spedas/spedas_agent_kit/spedas-workflow"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/spedas-workflow/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/spedas-workflow"><img src="https://agentmods.dev/badge/skills/spedas/spedas_agent_kit/spedas-workflow.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 | $0.00026 | $0.01093 |
| Opus 5.5 | $0.00010 | $0.00437 |
| Sonnet 5.5 | $0.00005 | $0.00219 |
| Haiku 4.5 | $0.00003 | $0.00109 |
Grade A, and why
spedas-workflow 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SPEDAS Agent Kit workflow
The plugin exposes one MCP server named spedas. Start with spedas_overview() when uncertain.
Prefer the public SPEDAS mental model:
- science workflow layer;
- unified data layer;
- data source categories:
cdaweb,pds,spice; - internal backend packages only when maintaining/debugging the MCP.
Preferred tools
search_spedas_data_sourcesplan_spedas_observationcompare_cdaweb_pds_spicecreate_spedas_analysis_bundlebrowse_data_sources(source_type="all"|"cdaweb"|"pds"|"spice")load_data_source(source_type, source_id)browse_data_parameters(source_type, dataset_id, ...)fetch_data_product(source_type, ...)manage_data_cache(source_type, ...)
Compatibility low-level tools remain available for maintenance/debugging, but new agent workflows should start with the unified data-layer tools.
MMS reconnection events (Batch 006 guardrail)
For MMS reconnection/EDR papers, keep the first pass narrow and explicit: plan
with spedas_overview / plan_spedas_observation, fetch burst FGM/FPI/EDP
artifacts, then chain into existing analysis helpers before asking for new code.
Use analyze_minvar_coordinates plus transform_timeseries_coordinates for LMN
or field-aligned panels, and use *-DIST artifacts with
compute_particle_spectra(..., spectrum_types=["energy", "pitch_angle"]) for
PAD/energy claims. A single-spacecraft e*n_e*(V_i-V_e) current or J·E' is a
transparent proxy, not a curlometer or paper-quality heating result; mark it
proxy unless the interval, LMN/FAC basis, calibrated E-field, and MMS1-4
curlometer diagnostics are all verified. If the paper/supplement interval cannot
be verified, record candidate_interval or availability_failure instead of
widening the fetch or claiming reproduction.
Heliospheric ICME/SEP multi-spacecraft events (Batch 007 guardrail)
For Wind/ACE/STEREO/OMNI ICME, magnetic-cloud, CME-CME, or SEP papers, use
paper-reproduction as the outer artifact contract and treat
docs/examples/stereo_icme_multispacecraft.md as the reduced first-pass recipe.
Start with STEREO MAG 1min + PLASTIC proton moments for multi-day events, add
Wind/ACE/OMNI only with explicit source/propagation labels, and keep SEP products
as reduced_sep_proxy until telescope/species/energy-channel metadata are
verified. Batch 007 confirmed that STEREO/PLASTIC/SEPT routing already exists;
the repeated gap is discoverability, event seeds, variable-alias provenance, and
overclaim prevention. Do not promote shock/sheath/cloud boundaries,
SEP onset/fluence, or SECCHI/HI J-map context to paper-quality outputs unless
those products and methods are explicitly loaded and documented.
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 · 85 lines · 26 tokens per session scan A d888ea4101d0
spedas-workflow is a skill published in the GitHub repository spedas/spedas_agent_kit (3 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 1,093 once invoked, about $0.0001 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.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
matlab
Builds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
exploratory-data-analysis
Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
phylogenetics
Builds and analyzes phylogenetic trees using MAFFT multiple sequence alignment, IQ-TREE maximum likelihood with ModelFinder and branch support, and FastTree approximate inference. Uses ETE3 for tree summaries and visualization. Applies to homologous nucleotide or protein sequences, microbial gene trees, protein…
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
presenting-conference-talks
Generates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. Use when preparing oral talks, spotlight presentations, or invited talks for ML and systems conferences.