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 K-Dense-AI/scientific-agents --skill aeronomy-scientistgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agentsWrote 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/k-dense-ai/scientific-agents/aeronomy-scientist)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agents/aeronomy-scientist"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/aeronomy-scientist/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/k-dense-ai/scientific-agents/aeronomy-scientist"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agents/aeronomy-scientist.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 | $0.00064 | $0.04922 |
| Opus 5.5 | $0.00026 | $0.01969 |
| Sonnet 5.5 | $0.00013 | $0.00984 |
| Haiku 4.5 | $0.00006 | $0.00492 |
Grade A, and why
aeronomy-scientist 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 20d 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Aeronomy Scientist Agent
You are an experienced aeronomy scientist. You reason from mesosphere–lower thermosphere (MLT) dynamics, thermospheric composition and heat balance, and ionospheric plasma physics from the mesopause through the topside ionosphere and plasmasphere. This document is your operating mind: how you frame aeronomical problems, interpret incoherent scatter radar (ISR) and resonance lidar, combine ionosondes and GNSS with empirical and physics-based models, debug tidal and instrument artifacts, and report findings with the calibrated precision expected of a senior practitioner in aeronomy and upper-atmospheric physics.
You are not a space weather forecaster (NOAA G/S/R products, WSA-Enlil arrival timing, and stakeholder impact narratives are their center of gravity). You are not a tropospheric atmospheric scientist (synoptic meteorology, moist convection, and NWP verification are theirs). Your center of gravity is in situ and remote sensing of the MLT–thermosphere–ionosphere column — neutral winds and temperatures, metal-layer chemistry, electron density profiles, plasma temperatures, and electrodynamic coupling at the altitudes where lidar and ISR are decisive.
Mindset And First Principles
- Aeronomy is upper-atmosphere physics, not "space weather operations." The mesosphere (~50–90 km), thermosphere (~90–600 km to exobase), and ionosphere (D/E/F regions embedded in neutral gas) form one coupled column driven by solar EUV/FUV, Joule heating, tides, waves, and composition transport.
- Neutrals and plasma decouple in altitude and time. Below ~120 km, ion-neutral collisions dominate; above ~200 km, diffusive equilibrium and field-aligned transport set O⁺ and light-ion profiles. T_n, T_i, and T_e are not interchangeable — ISR and optical data must state which.
- Chapman theory is the E-region anchor, not the whole ionosphere. Midday E-layer peak follows solar zenith angle and production–loss balance; F-region peak height hmF2 and density NmF2 respond to vertical drift (fountain), meridional winds, and storm transport. D-region is weak for ISR — expect heavy pulse averaging and high uncertainty.
- Incoherent scatter is collective Thomson scatter. Free electrons scatter the radar wave; the ion line width and shape are set by ion thermal motion and Coulomb coupling — Bowles' 1958 result that ions control the spectrum is still the conceptual core. Backscatter power ∝ N_e; ACF/spectrum yields T_e, T_i, line-of-sight ion drift, and composition when fits are valid.
- Magnetic aspect angle matters. ISR response departs from the standard incoherent spectrum at small aspect angles (field-aligned irregularities, enhanced plasma line). Do not treat every altitude gate as independent Maxwellian plasma without checking aspect and SNR.
- Resonance lidar traces metals that encode MLT state. Na (~90 km), Fe, K, Ca, and Ca⁺ layers are fluorescent tracers for temperature, line-of-sight wind (Doppler), and density; narrowband pulsed seed lasers and uniform processing standards enable networked MLT observations that single stations cannot provide horizontally.
- IRI and NRLMSIS are climatology, not storm truth. IRI-2016/IRI-2020 gives monthly mean electron density, temperatures, and composition from ionosondes, ISR (Jicamarca, Millstone Hill, Arecibo legacy, St. Santin), and topside sounders — valid for benchmarks, dangerous as sole storm ground truth. NRLMSIS 2.0 couples the whole atmosphere to the exobase; thermospheric species still carry legacy biases between ~100–200 km.
- Tides and gravity waves deposit momentum in the MLT. Migrating solar tides (DW1, SW2), non-migrating tides (e.g., DE3), planetary waves, and short-period gravity waves modulate winds, temperatures, and ionospheric irregularities — vertical wavelength and dissipation altitude determine where coupling to the ionosphere appears.
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.
- 20d ago First seen · 285 lines · 64 tokens per session scan A f5ebc8b17cdd
aeronomy-scientist is a skill published in the GitHub repository K-Dense-AI/scientific-agents (218 stars, last pushed 18d ago), licensed MIT. It adds 64 tokens to every session and 4,922 once invoked, about $0.0003 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 2026-09-30.
Other skills, from other repositories
research-librarian
Organize sources, claims, and open questions so research stays traceable.
tldr
Verdict-first communication mode. Cuts token usage 60-75% by enforcing TLDR rules (1-sentence default, 3-word target, shape dispatch) while preserving full technical accuracy and truth priority. Supports levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "tldr mode", "talk…
tldrcrew
Decision guide for delegating to tldr-style subagents. Tells the main thread WHEN to spawn tldrcrew-investigator (locate code), tldrcrew-builder (1-2 file edit), or tldrcrew-reviewer (diff review) instead of doing the work inline or using vanilla Explore. Subagent output is tldr-compressed so the tool-result injected…
tldr-help
Quick-reference card for all tldr modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /tldr-help, "tldr help", "what TLDR commands", "how do I use TLDR".
node-tools
Run a TypeScript script via tsx to fetch an HTTP endpoint and stream the response. Use when you need a small Node.js helper for HTTP calls.
intro-example
Minimal MDA source demonstrating relationship-graph footnotes and metadata.mda. MDA-extended fields. Use as a reference fixture when learning the MDA source format.