Individual skill
physics-pro
Applied physics problem-solving — mechanics, E&M, statistical mechanics, and data analysis with real unit and error discipline.
skills/physics-pro/SKILL.md
Source commit faf37c0859ebf627bfcb5225e8057d088691e0ae
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 8, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 54
- Repository last updated
- Oct 10, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- ai-agents-automation Repository topic
- ai-skills Repository topic
- awesome Repository topic
- awesome-list Repository topic
- chatgpt Repository topic
- claude-skills Repository topic
- meta-ai Repository topic
- muse-ai Repository topic
- data Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Read excerpt
## Overview
Physics-pro is a practical companion for doing physics: setting up problems
correctly (units, scales, symmetries), choosing the right formalism
(Lagrangian vs Newtonian, circuit vs field picture), analyzing experimental
data with honest error propagation, and sanity-checking results with
dimensional analysis and limiting cases.
## When to use
- Solving mechanics/E&M/thermo problems: choose coordinates, identify conserved quantities, set up equations of motion
- Designing or debugging experiments: sensor choice, noise budgets, calibration strategy
- Analyzing data: fitting models, propagating uncertainties, comparing theory to measurement
- Estimating before calculating: order-of-magnitude checks, scaling laws, Fermi problems