sympy-symbolic-math SKILL.md skillA
sympy-symbolic-math from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/sympy-symbolic-math@git:20260428.81ea2d2Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/scientific-computing/sympy-symbolic-math/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260428.81ea2d2, committed Apr 28, 2026
- First version recorded
- Feb 18, 2026
- Size
- 15,729 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Symbolic math in Python: exact algebra, calculus (derivatives, integrals, limits), equation solving, symbolic matrices, ODEs, code gen (lambdify, C/Fortran). Use for exact symbolic results. For numerical use numpy/scipy; for stats use statsmodels.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# SymPy — Symbolic Mathematics ## Overview SymPy is a Python library for symbolic mathematics that performs exact computation using mathematical symbols rather than numerical approximations. It covers algebra, calculus, equation solving, linear algebra, physics, and code generation — all within pure Python with no external dependencies. ## When to Use - Solving equations symbolically (algebraic, systems, differential equations) - Performing calculus operations (derivatives, integrals, limits, series expansions) - Simplifying and manipulating algebraic expressions - Working with matrices symbolically (eigenvalues, determinants, decompositions) - Converting symbolic expressions to fast numerical functions (lambdify → NumPy) - Generating code from math expressions (C, Fortran, LaTeX) - Needing exact results (e.g., `sqrt(2)` not `1.414...`) - For **numerical computing** (array operations, linear algebra on data), use numpy/scipy - For **statistical modeling** (regression, hypothesis testing), use statsmodels ## Prerequisites ```bash pip install sympy # Optional for numerical evaluation: pip install numpy matplotlib ``` …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/sympy-symbolic-math@sha256:d21f854ec2a17a96The line at the top of this page pins the label git:20260428.81ea2d2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_dkl5mvbuifa2pwv3)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260428.81ea2d2 latest | 2026-04-28 | 81ea2d2 | 15,729 B | A | view · diff |
| git:20260218.e460066 | 2026-02-18 | e460066 | 15,828 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (15729 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_dkl5mvbuifa2pwv3 GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/sympy-symbolic-math GET https://markdownregistry.com/api/v1/blob/d21f854ec2a17a96b9df53214d8ea4a08715fae766b8f2024415380b31e48c0b
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.