evaluate-levitation-mechanism
Acerca de
Esta habilidad realiza un estudio estructurado de alternativas para evaluar y comparar diferentes mecanismos de levitación—incluyendo tipos magnéticos, acústicos, aerodinámicos y electrostáticos—para una aplicación específica. Úsela al seleccionar el enfoque de levitación óptimo para tareas como transporte, medición de precisión o manipulación de muestras. Proporciona un análisis sistemático para guiar la toma de decisiones técnicas.
Instalación rápida
Claude Code
Recomendadonpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/evaluate-levitation-mechanismCopia y pega este comando en Claude Code para instalar esta habilidad
Documentación
Evaluate Levitation Mechanism
Select appropriate levitation mechanism → define reqs, screen hard constraints, score survivors soft, document reproducible trade study.
Use When
- Choose approach new product/experiment
- Compare magnetic/acoustic/aerodynamic/electrostatic for contactless handling
- Justify design in review/proposal
- Re-evaluate existing when reqs change (new payload, env, cost)
- Feasibility study before detailed design
In
- Required: Application (what levitated, why contactless)
- Required: Payload (mass, material, geometry, temp sensitivity)
- Required: Env (temp, atmosphere, cleanliness, vibration)
- Optional: Power budget (W)
- Optional: Cost target (prototype + prod)
- Optional: Precision (position accuracy, stiffness, vib iso)
- Optional: Lifetime + maintenance
Do
Step 1: Requirements
All reqs before evaluate.
- Payload: Mass (min-max), dims, material, magnetic props (ferro? conductive? diamagnetic?), temp limits (cryo? heat?), surface sensitivity (contact = contamination/damage?).
- Performance: Gap (mm-m), load capacity, accuracy, stiffness (N/m), damping, dynamic range (static hold vs controlled motion).
- Env constraints: Temp range, atmosphere (air, vacuum, inert, liquid), cleanliness (fab, biological, industrial), acoustic noise, EMC.
- Op constraints: Power, envelope (size + weight of system), maintenance interval, lifetime, operator skill.
- Economic: Prototype cost, unit cost prod, dev timeline.
## Requirements Summary
| Category | Requirement | Value | Priority |
|----------|------------|-------|----------|
| Payload mass | Range | [min - max] kg | Must have |
| Payload material | Magnetic class | [ferro/para/dia/non-magnetic] | Must have |
| Gap | Levitation height | [value] mm | Must have |
| Precision | Position accuracy | [value] um | Want |
| Temperature | Operating range | [min - max] C | Must have |
| Power | Budget | [value] W | Want |
| Cost | Unit cost target | [value] | Want |
| Environment | Cleanliness | [class or none] | Must have |
| Noise | Acoustic limit | [value] dB | Want |
| EMC | Field emission limit | [value or none] | Want |
→ Req table each classified "Must have" (hard, pass/fail) or "Want" (soft, scored). ≥5 reqs.
If err: vague → interview or boundary analysis (loosest acceptable). No reqs → arbitrary/biased study.
Step 2: Catalog Candidates
Mechanisms + principles + limits.
-
Passive diamagnetic: Diamagnetic susceptibility in permanent magnet. No power. Small (mg-g) w/ strong diamagnetic (pyrolytic graphite, bismuth). Room temp.
-
Active EM feedback: Electromagnets + sensors + controller. g-100+t (maglev). Continuous power + control. Ferro/conductive.
-
Superconducting: Type-II SC + flux pinning → passive, powerless, stable. Cryo (LN2 YBCO 77K, LHe conventional). Payload limited by SC size + critical current. Extremely stiff.
-
Acoustic standing wave: Ultrasonic transducers → pressure nodes trap small. Sub-wavelength (<5mm in air at 40kHz). Continuous drive. Any material regardless magnetic/electrical. Audible harmonics + acoustic streaming.
-
Acoustic phased array: Multiple indep transducers → 3D manipulation + repositioning. Higher complex/cost, great flex.
-
Aerodynamic (air bearings): Thin pressurized air film. Precision stages, air hockey, hovercraft. Continuous air. Very low friction. Gap 5-25μm precision, larger hovercraft.
-
Aerodynamic (Coanda/Bernoulli): Jet over curved surface → low-pressure suspends. Simple + inexpensive. Low precision/stiffness. Demos + industrial handling.
-
Electrostatic (Coulomb): Charged electrodes suspend charged/dielectric. Very low force (μN-mN). Vacuum ok. Space (grav wave detectors, inertial sensors), MEMS.
-
Electrostatic (ion trap): Oscillating E fields (Paul) or static+B (Penning) confine charged particles. Single ions-nanoparticles. Lab technique atomic physics + mass spec.
## Candidate Mechanisms
| # | Mechanism | Payload Range | Power | Temperature | Any Material? |
|---|-----------|--------------|-------|-------------|--------------|
| 1 | Passive diamagnetic | mg - g | None | Room temp | No (diamagnetic only) |
| 2 | Active EM feedback | g - 100+ t | Continuous | Room temp | No (ferro/conductive) |
| 3 | Superconducting | g - kg | Cryocooler | < 77 K | No (above SC) |
| 4 | Acoustic standing wave | ug - g | Continuous | Room temp | Yes |
| 5 | Acoustic phased array | ug - g | Continuous | Room temp | Yes |
| 6 | Air bearing | g - t | Air supply | Room temp | Yes |
| 7 | Coanda/Bernoulli | g - kg | Air supply | Room temp | Yes |
| 8 | Electrostatic Coulomb | ug - mg | Minimal | Any (vacuum ok) | No (charged/dielectric) |
| 9 | Ion trap | atoms - ug | RF power | Any (vacuum) | No (ions only) |
→ Catalog all plausible mechanisms + fundamental chars. ≥4 mechanisms ≥2 physical principles.
If err: fundamental limits uncertain → consult lit or related skills (analyze-magnetic-levitation, design-acoustic-levitation). No screen by guess.
Step 3: Screen Hard Constraints
Eliminate mechanisms failing any "Must have".
- Each hard constraint = pass/fail. Single fail eliminates.
- Common screens:
- Mass: Payload exceeds limit → eliminate (acoustic can't handle kg).
- Material: Non-magnetic + requires magnetic → eliminate.
- Temp: Cryo infeasible → eliminate SC.
- Vacuum/atm: Vacuum → eliminate aero. No-magnetic-fields EMC → eliminate magnetic.
- Contact: Air bearings need proximity to flat. True non-contact → eliminate.
- Document eliminations + reasons → can revisit if reqs change.
## Screening Results
| # | Mechanism | Pass/Fail | Eliminating Constraint | Reason |
|---|-----------|-----------|----------------------|--------|
| 1 | Passive diamagnetic | [P/F] | [constraint or N/A] | [reason] |
| 2 | Active EM feedback | [P/F] | [constraint or N/A] | [reason] |
| ... | ... | ... | ... | ... |
→ Reduced list passed all hard. ≥1 survives; ideally 2-4 for scoring.
If err: none pass → reqs mutually contradictory. Relax least critical "Must have" (→"Want") + re-screen. Multiple relax → may need hybrid (magnetic primary + aero stabilization).
Step 4: Score Soft Criteria
Rank survivors via weighted matrix.
- Define criteria + weights: Convert "Want" → scoring criterion. Weights reflect importance (1-5 or % summing 100%). Common:
- Cost (prototype + unit): weight by economic sensitivity
- Complexity: components, electronics, alignment criticality
- Precision: accuracy, stiffness, vib iso
- Power: op W, standby W
- Scalability: payload range, manufacturability
- Controllability: ease adjust gap/position/stiffness dynamically
- Maturity: TRL, commercial component availability
- Noise: acoustic, EM, vibration emissions
- Score each: Consistent scale (1=poor, 3=adequate, 5=excellent). Quant data Steps 1-3 not subjective.
- Weighted: Score × weight, sum. Highest = top.
- Sensitivity: Vary top 2-3 weights ±20%. Ranking change? If sensitive → flag, present alts.
## Scoring Matrix
| Criterion | Weight | Mech A | Mech B | Mech C |
|-----------|--------|--------|--------|--------|
| Cost | [w1] | [s1A] | [s1B] | [s1C] |
| Complexity | [w2] | [s2A] | [s2B] | [s2C] |
| Precision | [w3] | [s3A] | [s3B] | [s3C] |
| Power | [w4] | [s4A] | [s4B] | [s4C] |
| Scalability | [w5] | [s5A] | [s5B] | [s5C] |
| Controllability | [w6] | [s6A] | [s6B] | [s6C] |
| Maturity | [w7] | [s7A] | [s7B] | [s7C] |
| **Weighted Total** | | **[T_A]** | **[T_B]** | **[T_C]** |
| **Rank** | | [rank] | [rank] | [rank] |
→ Complete matrix all weighted + scored. Clear rank, top candidate. Sensitivity confirms robust (or fragile documented).
If err: 2 mechanisms within 10% → too close on paper. Prototype both + select on experiment, or identify discriminating test.
Step 5: Document Recommendation
Final trade study.
- Recommendation: Recommended mechanism + 1-paragraph justification referencing scoring + key discriminators.
- Runner-up: 2nd place + conditions under which it becomes preferred (fallback).
- Eliminated: List + disqualifying constraints for completeness.
- Risks + mitigations: Recommended → top 3 risks + mitigations.
- Next steps: Detailed design work (analyze-magnetic-levitation, design-acoustic-levitation, etc.).
## Trade Study Summary
### Recommendation
**[Mechanism name]** is recommended for [application] because [2-3 sentence justification
referencing the key scoring advantages].
### Runner-Up
**[Mechanism name]** would be preferred if [condition changes, e.g., "cryogenics become
available" or "payload mass decreases below X grams"].
### Eliminated Mechanisms
- [Mechanism]: eliminated by [constraint]
- [Mechanism]: eliminated by [constraint]
### Risks
| Risk | Impact | Likelihood | Mitigation |
|------|--------|-----------|------------|
| [Risk 1] | [H/M/L] | [H/M/L] | [action] |
| [Risk 2] | [H/M/L] | [H/M/L] | [action] |
| [Risk 3] | [H/M/L] | [H/M/L] | [action] |
### Next Steps
1. [Detailed analysis using specific skill]
2. [Prototype or simulation task]
3. [Experimental validation milestone]
→ Self-contained doc other engineer could review/challenge/act. Recommendation traceable to reqs + scoring not unstated prefs.
If err: recommendation can't be justified by scoring alone (top has showstopper criteria missed) → revisit Step 1, add missing req. No override scoring w/o documenting.
Check
- Reqs quant + priority classified
- ≥4 mechanisms ≥2 physical principles
- Hard screen consistent + documented
- ≥2 mechanisms survive for compare
- Criteria explicit weights, scores justified
- Sensitivity on top 2-3 weights
- Recommendation traceable to matrix
- Runner-up + fallback documented
- Risks + mitigations
- Study complete for indep review
Traps
- Anchor preferred mechanism first: Start w/ conclusion, reverse-engineer reqs/weights. Cure: reqs + weights before eval. If know what want → validation not selection, be honest.
- Omit mechanisms unfamiliar domains: Magnetic engineers overlook acoustic + vice versa. Include ≥1 from 4 families (magnetic, acoustic, aerodynamic, electrostatic) even if screened out.
- Confuse hard/soft: Preference as hard eliminates viable early. Only non-negotiable (safety, physics, regulatory) = hard. Rest scored.
- Equal weighting default: Same weight = decision (all equal). Stakeholders prioritize. Refuse → pairwise (AHP) to elicit implicit.
- Ignore system-level: Mechanism not isolated. Acoustic → noise affects instruments. Active magnetic → time-varying fields violate EMC. SC → cryo infra. Evaluate in system context.
- Single-point score no uncertainty: "4" on cost = false precision. Express ranges ("3-5"), propagate uncertainty. 2 mechanisms overlap → rank not definitive.
→
analyze-magnetic-levitation— detailed analysis magnetic recommended/candidatedesign-acoustic-levitation— detailed design acoustic selectedanalyze-magnetic-field— compute field profiles for magnetic assessmentargumentation— structured reasoning + decision justification
Repositorio GitHub
Habilidades relacionadas
llamaguard
OtroLlamaGuard es el modelo de Meta de 7-8B parámetros para moderar las entradas y salidas de LLM en seis categorías de seguridad como violencia y discurso de odio. Ofrece una precisión del 94-95% y puede implementarse usando vLLM, Hugging Face o Amazon SageMaker. Utiliza esta skill para integrar fácilmente filtrado de contenido y barreras de seguridad en tus aplicaciones de IA.
cost-optimization
OtroEsta Skill de Claude ayuda a los desarrolladores a optimizar los costes en la nube mediante el ajuste de tamaño de recursos, estrategias de etiquetado y análisis de gastos. Proporciona un marco para reducir los gastos en la nube e implementar una gobernanza de costes en AWS, Azure y GCP. Úsala cuando necesites analizar los costes de infraestructura, ajustar el tamaño de los recursos o cumplir con restricciones presupuestarias.
quantizing-models-bitsandbytes
OtroEsta habilidad cuantiza LLMs a precisión de 8 o 4 bits utilizando bitsandbytes, logrando una reducción de memoria del 50-75% con pérdida mínima de precisión. Es ideal para ejecutar modelos más grandes en memoria GPU limitada o para acelerar la inferencia, admitiendo formatos como INT8, NF4 y FP4. La habilidad se integra con HuggingFace Transformers y permite entrenamiento QLoRA y optimizadores de 8 bits.
dispatching-parallel-agents
OtroEsta Skill de Claude despliega múltiples agentes para investigar y solucionar 3 o más problemas independientes de forma concurrente. Está diseñada para escenarios que involucran fallos no relacionados que pueden resolverse sin estado compartido o dependencias. Su capacidad principal es la resolución paralela de problemas, asignando un agente por cada dominio problemático independiente para maximizar la eficiencia.
