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 design-acoustic-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/design-acoustic-levitation)<a href="https://agentmods.dev/skills/pjt222/agent-almanac/design-acoustic-levitation"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/design-acoustic-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/design-acoustic-levitation"><img src="https://agentmods.dev/badge/skills/pjt222/agent-almanac/design-acoustic-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 | $0.00083 | $0.04176 |
| Opus 5 | $0.00042 | $0.02088 |
| Sonnet 5 | $0.00017 | $0.00835 |
| Haiku 4.5 | $0.00008 | $0.00418 |
Grade A, and why
design-acoustic-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 9d 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 — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Acoustic Levitation
Design and validate an acoustic levitation system by determining the acoustic radiation pressure required to balance gravity, selecting transducer and reflector geometry to form a stable standing wave, computing the positions and trapping strength of pressure nodes, and verifying that the trapped object is stable against lateral and axial perturbations.
When to Use
- Designing a contactless sample holder for chemical or biological experiments
- Building an acoustic levitation demonstrator for education or outreach
- Evaluating whether a given object can be levitated acoustically (size, density, and frequency constraints)
- Selecting between single-axis (transducer-reflector) and phased array configurations
- Calculating the node positions and trapping forces for a given transducer frequency and geometry
- Extending a single-axis levitator to multi-axis manipulation using phased arrays
Inputs
- Required: Object properties (mass, density, radius or characteristic dimension, compressibility if known)
- Required: Target levitation medium (air, water, inert gas) with its density and speed of sound
- Optional: Available transducer frequency (default: 40 kHz, common for hobbyist and lab systems)
- Optional: Transducer power or voltage rating
- Optional: Desired manipulation capability (static trapping only, or dynamic repositioning)
Procedure
Step 1: Determine Object Properties and Acoustic Contrast
Characterize the object and the medium to establish the fundamental feasibility of acoustic levitation:
- Object parameters: Record the mass m, density rho_p, radius a (or equivalent sphere radius for non-spherical objects), and bulk modulus K_p (compressibility kappa_p = 1/K_p). For rigid objects like metal spheres, K_p is effectively infinite.
- Medium parameters: Record the density rho_0, speed of sound c_0, and bulk modulus K_0 = rho_0 * c_0^2 for the host medium.
- Acoustic contrast factor: Compute the Gor'kov contrast factors that determine whether the object migrates to pressure nodes or antinodes:
- Monopole coefficient: f_1 = 1 - (K_0 / K_p) = 1 - (rho_0 * c_0^2) / (rho_p * c_p^2)
- Dipole coefficient: f_2 = 2 * (rho_p - rho_0) / (2 * rho_p + rho_0)
- For most solid objects in air, f_1 ~ 1 and f_2 ~ 1, so the object is trapped at pressure nodes (velocity antinodes).
- Size constraint: Verify that the object radius a is much smaller than the acoustic wavelength lambda = c_0 / f. The Gor'kov theory requires a << lambda (typically a < lambda/4). If this condition is not met, ray acoustics or full numerical simulation is needed.
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.
- 9d ago First seen · 209 lines · 83 tokens per session scan A 5667299fdf46
design-acoustic-levitation is a skill published in the GitHub repository pjt222/agent-almanac (33 stars, last pushed 2d ago), licensed MIT. It adds 83 tokens to every session and 4,176 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 2026-09-03.
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…
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".
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".
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".
product-audit
Audit the whole product across code, quality, process, docs, roadmap, and tooling. Persist one severity-ranked, F-numbered report with proposals; never fix or file work. Triggers: "product-audit", "audit the product", "full health check", "are we product-ready", "CTO review".