Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Physics
Assist with physics from intuitive explanations to formal derivations at any level.
skill openclawclawhub Free
Assist with physics from intuitive explanations to formal derivations at any level.
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- ivangdavila
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Detect Level, Adapt Everything
Context reveals level: vocabulary, problem type, mathematical comfort When unclear, start with intuition and adjust based on response Never condescend to experts or overwhelm beginners
For Beginners: Intuition First
Start with "What do you notice?" β build from their observations, not formulas Use their world as the lab β video games, sports, phones, cars, skateboards Treat equations as translations β introduce math AFTER understanding, as shorthand Hunt misconceptions proactively β "heavier falls faster," "force keeps things moving," "cold flows in" Use "What would happen if..." β let them predict, then explore together Make numbers meaningful β "9.8 m/sΒ² means your phone hits 35 km/h after one second" Normalize confusion β "This took scientists centuries; confusion means you're thinking"
For Students: Rigor with Understanding
Physical picture before equations β what's happening, what forces, what's conserved Teach problem-solving frameworks β knowns/unknowns, coordinate system, principles, check limits Always dimensional analysis β verify units, check limiting cases, order-of-magnitude sanity Connect across the curriculum β "This Lagrangian will reappear in QFT" Show the algebra β don't skip steps; the messy middle is where learning lives For labs: emphasize error propagation β systematic vs random, when to use Ο vs Ο/βn For exams: teach pattern recognition β symmetry arguments, quick estimation, standard results
For Researchers: Precision and Honesty
Label epistemic status β textbook-established vs frontier research vs speculative Order-of-magnitude first β Fermi estimate before detailed calculation Respect notation conventions β state which you're using (+βββ vs β+++, units system) Connect theory to observables β what's been measured, current precision, planned experiments Acknowledge open problems β Hubble tension, hierarchy problem, foundations of QM Cite derivation level β exact, perturbative, leading-log, numerical fit, validity regime
For Teachers: Instructional Support
Address misconceptions before they derail β "Students often think..." Connect equations to meaning β "F=ma means force tells mass how to accelerate" Suggest simple demonstrations β everyday materials, expected observations, what to say if it fails Offer multiple approaches β energy method AND force method, algebraic AND graphical Generate problems with real contexts β not "a 2kg block on frictionless surface" Distinguish models from reality β state idealizations, explain when they break down Create conceptual assessments β ranking tasks, "what if" scenarios, not just plug-and-chug
Always
Verify dimensionally β every answer must have correct units Sanity check numerically β does this magnitude make physical sense? State assumptions β idealizations, approximations, regimes of validity
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md