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 pjt222/agent-almanac --skill analyze-magnetic-levitationgit clone --depth 1 https://github.com/pjt222/agent-almanacWrote 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/pjt222/agent-almanac/analyze-magnetic-levitation)<a href="https://agentmods.dev/skills/pjt222/agent-almanac/analyze-magnetic-levitation"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/analyze-magnetic-levitation/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/pjt222/agent-almanac/analyze-magnetic-levitation"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/analyze-magnetic-levitation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00105 | $0.03875 |
| Opus 5 | $0.00053 | $0.01937 |
| Sonnet 5 | $0.00021 | $0.00775 |
| Haiku 4.5 | $0.00011 | $0.00387 |
Grade A, and why
analyze-magnetic-levitation 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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Magnetic Levitation
Determine whether a given magnetic system can achieve stable levitation, identify which physical mechanism enables or forbids it, calculate the conditions for force balance and stability, and verify that the levitation is stable against perturbations in all spatial degrees of freedom including tilting modes.
When to Use
- Evaluating whether a proposed magnetic levitation design is physically viable
- Determining why a permanent magnet arrangement fails to levitate and identifying a workaround
- Analyzing superconducting levitation systems (Meissner effect, flux pinning, mixed-state trapping)
- Designing or troubleshooting active electromagnetic feedback levitation (maglev trains, magnetic bearings)
- Assessing diamagnetic levitation feasibility for a given material and field strength
- Understanding spin-stabilized magnetic levitation (Levitron) dynamics
Inputs
- Required: Description of the levitated object (mass, geometry, magnetic moment or susceptibility)
- Required: Description of the field source (permanent magnets, electromagnets, superconducting coils, arrangement geometry)
- Optional: Operating environment (temperature, vacuum, vibration constraints)
- Optional: Desired levitation height or gap
- Optional: Stability requirements (stiffness, damping, bandwidth for active systems)
Procedure
Step 1: Characterize the System
Establish the complete physical description of the object and field source before any analysis:
- Object properties: Record the mass m, geometry (sphere, disk, rod), magnetic moment mu (for permanent magnet objects), volume magnetic susceptibility chi_v (for paramagnetic, diamagnetic, or ferromagnetic materials), and electrical conductivity sigma (relevant for eddy current effects).
- Field source properties: Describe the source configuration -- permanent magnet array (Halbach, dipole, quadrupole), electromagnet with coil parameters (turns, current, core material), or superconducting coil (critical current, critical field).
- Field geometry: Determine the spatial profile of the magnetic field B(r). Identify the field gradient dB/dz along the levitation axis and the curvature d^2B/dz^2 that governs stability.
- Environmental constraints: Note temperature range (cryogenic for superconductors), atmosphere (vacuum reduces damping), and vibration spectrum.
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 · 214 lines · 105 tokens per session scan A 2bfff55edcbe
analyze-magnetic-levitation is a skill published in the GitHub repository pjt222/agent-almanac (32 stars, last pushed yesterday), licensed MIT. It adds 105 tokens to every session and 3,875 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 2026-09-03.
Other skills, from other repositories
analytics
Queries local analytics across OrchestKit projects for agent usage, skill frequency, hook timing, team activity, session replay, cost estimation, and model delegation trends. Privacy-safe with hashed project IDs. Supports time-range filtering and comparative analysis. Use when reviewing performance, estimating costs…
astro-dso-doc
Generates a complete, polished HTML documentation page, a processing checklist, an AstroBin post JSON, a PixInsight process icon set (XPSM), AND a ready-to-paste PixInsight project Description field for a deep-sky object (DSO) astrophotography project. Use this skill whenever the user mentions astrophotography, a DSO…
design-feature
Turn a raw idea or existing feature into a designed product SPEC by completing entity, integration, role, and expectation closure. Upserts never destroy recorded decisions. Triggers: "design-feature", "design this feature", "define product scope".
audit-pr
Audit a whole PR against the delivery contract and return MERGE-READY or evidenced blockers with the full URL. Consumes the current review-change REVIEW-PASS receipt instead of re-running review axes; posts a SHA-bound ready comment; never edits or merges. Triggers: "audit-pr", "is this PR ready", "merge gate".
fold-findings
Repair persisted fix-now findings in compatible atomic batches: root-cause fixes, green gate, commit/push, and per-row folded: yes updates. Never reclassify or substitute backlog notes. Triggers: "fold-findings", "fix the review findings", "repair audit blockers".
plan-feature
Route designed features or issues into engineering planning and roadmap registration; undesigned work stops at design-feature. Supports --next, --from-issue, and --scaffold. Triggers: "plan-feature", "plan a feature", "plan the next roadmap feature", "create SPEC and TASKS".