How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does math support?

math works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Yes. math is free to install and use. It is available from the open explainx.ai skill registry published by parcadei.

Where can I read ratings and reviews for math?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install math?

Run `npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math` in your terminal. You need to have run `npx skills init` once in your project first.

Productivity

math▌

parcadei/continuous-claude-v3 · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math

0 commentsdiscussion

summary

One entry point for all computation and explanation. I route to the right tool based on your request.

skill.md

/math - Unified Math Capabilities

One entry point for all computation and explanation. I route to the right tool based on your request.

For formal proofs, use /prove instead.

Quick Examples

You Say	I Use
"Solve x² - 4 = 0"	SymPy solve
"Integrate sin(x) from 0 to π"	SymPy integrate
"Eigenvalues of [[1,2],[3,4]]"	SymPy eigenvalues
"Is x² + 1 > 0 for all x?"	Z3 prove
"Convert 5 miles to km"	Pint
"Explain what a functor is"	Category theory skill

Computation Scripts

SymPy (Symbolic Math)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" <command> <args>

Command	Description	Example
`solve`	Solve equations	`solve "x**2 - 4" --var x`
`integrate`	Definite/indefinite integral	`integrate "sin(x)" --var x --lower 0 --upper pi`
`diff`	Derivative	`diff "x**3" --var x`
`simplify`	Simplify expression	`simplify "sin(x)2 + cos(x)2"`
`limit`	Compute limit	`limit "sin(x)/x" --var x --point 0`
`series`	Taylor expansion	`series "exp(x)" --var x --point 0 --n 5`
`dsolve`	Solve ODE	`dsolve "f''(x) + f(x)" --func f --var x`
`laplace`	Laplace transform	`laplace "sin(t)" --var t`

Matrix Operations:

Command	Description
`det`	Determinant
`eigenvalues`	Eigenvalues
`eigenvectors`	Eigenvectors with multiplicities
`inverse`	Matrix inverse
`transpose`	Transpose
`rref`	Row echelon form
`rank`	Matrix rank
`nullspace`	Null space basis
`linsolve`	Linear system Ax=b
`charpoly`	Characteristic polynomial

Number Theory:

Command	Description
`factor`	Factor polynomial
`factorint`	Prime factorization
`isprime`	Primality test
`gcd`	Greatest common divisor
`lcm`	Least common multiple
`modinverse`	Modular inverse

Combinatorics:

Command	Description
`binomial`	C(n,k)
`factorial`	n!
`permutation`	P(n,k)
`partition`	Integer partitions p(n)
`catalan`	Catalan numbers
`bell`	Bell numbers

Z3 (Constraint Solving)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/z3_solve.py" <command> <args>

Command	Use Case
`sat`	Is this satisfiable?
`prove`	Is this always true?
`optimize`	Find min/max subject to constraints

Pint (Units)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/pint_compute.py" convert <value> <from_unit> <to_unit>

Example: convert 5 miles kilometers

Math Router (Auto-Route)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/math_router.py" route "<natural language request>"

Returns the exact command to run. Use when unsure which script.

Topic Skills (For Explanation)

When the request is "explain X" or "what is X", I reference these:

Topic	Skill Location	Key Concepts
Abstract Algebra	`math/abstract-algebra/`	Groups, rings, fields, homomorphisms
Category Theory	`math/category-theory/`	Functors, natural transformations, limits
Complex Analysis	`math/complex-analysis/`	Analytic functions, residues, contour integrals
Functional Analysis	`math/functional-analysis/`	Banach spaces, operators, spectra
Linear Algebra	`math/linear-algebra/`	Matrices, eigenspaces, decompositions
Mathematical Logic	`math/mathematical-logic/`	Propositional, predicate, proof theory
Measure Theory	`math/measure-theory/`	Lebesgue, σ-algebras, integration
Real Analysis	`math/real-analysis/`	Limits, continuity, convergence
Topology	`math/topology/`	Open sets, compactness, connectedness
ODEs/PDEs	`math/odes-pdes/`	Differential equations, boundary problems
Optimization	`math/optimization/`	Convex, LP, gradient methods
Numerical Methods	`math/numerical-methods/`	Approximation, error analysis
Graph/Number Theory	`math/graph-number-theory/`	Graphs, primes, modular arithmetic
Information Theory	`math/information-theory/`	Entropy, coding, channels

Routing Logic

I decide based on your request:

"solve/calculate/compute" → SymPy (exact symbolic)
"is X always true?" → Z3 (constraint proving)
"convert units" → Pint
"explain/what is" → Topic skill for context
"prove formally" → Redirect to /prove

Examples

Solve Equation

User: Solve x² - 5x + 6 = 0
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" solve "x**2 - 5*x + 6" --var x
Result: x = 2 or x = 3

Compute Eigenvalues

User: Find eigenvalues of [[2, 1], [1, 2]]
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" eigenvalues "[[2,1],[1,2]]"
Result: {1: 1, 3: 1}  (eigenvalue 1 with multiplicity 1, eigenvalue 3 with multiplicity 1)

Prove Inequality

User: Is x² + y² ≥ 2xy always true?
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/z3_solve.py" prove "x**2 + y**2 >= 2*x*y"
Result: PROVED (equivalent to (x-y)² ≥ 0)

Convert Units

User: How many kilometers in 26.2 miles?
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/pint_compute.py" convert 26.2 miles kilometers
Result: 42.16 km

When to Use /prove Instead

Use /prove when you need:

Machine-verified formal proof (Lean 4)
Category theory proofs (functors, Yoneda, etc.)
Publication-quality verification
Abstract algebra proofs

/math is for computation. /prove is for verification.

how to use math

How to use math on Cursor

AI-first code editor with Composer

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add math

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill math

The skills CLI fetches math from GitHub repository parcadei/continuous-claude-v3 and configures it for Cursor.

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ── always included ────

│ • Amp

│ • Antigravity

│ • Cline

│ • Codex

│ ●Cursor(selected)

│ • Cursor

│ • Windsurf

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/math

Reload or restart Cursor to activate math. Access the skill through slash commands (e.g., /math) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub ›Skills CLI documentation ›Learn more about Cursor ›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

✓

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

✓

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

✓

Save 3-5 hours/week on communication overhead

Implementation Guide▌

Prerequisites

›Claude Desktop or compatible AI client
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

1.Install product management skill
2.Start with user story generation for known feature
3.Progress to competitive analysis: research 2-3 competitors
4.Use for roadmap prioritization: apply RICE/ICE scoring
5.Draft stakeholder communications and refine based on feedback
6.Build template library for recurring PM tasks
7.Share effective prompts with product team

Common Pitfalls

⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements

Best Practices▌

✓ Do

+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition

✗ Don't

−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture

💡 Pro Tips

★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs

When to Use This▌

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path▌

1Basic: user stories, feature specs, status updates
2Intermediate: competitive analysis, prioritization frameworks, PRDs
3Advanced: product strategy, go-to-market planning, OKR setting
4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)

No comments yet — start the thread.

general reviews

Ratings

4.5★★★★★71 reviews

★★★★★Alexander Diallo· Dec 28, 2024
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.
★★★★★Sofia Ramirez· Dec 24, 2024
Registry listing for math matched our evaluation — installs cleanly and behaves as described in the markdown.
★★★★★Aanya Torres· Dec 20, 2024
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.
★★★★★Aditi Haddad· Dec 16, 2024
Keeps context tight: math is the kind of skill you can hand to a new teammate without a long onboarding doc.
★★★★★Dhruvi Jain· Dec 8, 2024
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.
★★★★★Mateo Smith· Dec 8, 2024
We added math from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
★★★★★Luis Patel· Dec 4, 2024
math has been reliable in day-to-day use. Documentation quality is above average for community skills.
★★★★★Liam Rao· Dec 4, 2024
math is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
★★★★★Oshnikdeep· Nov 27, 2024
We added math from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
★★★★★Min Martinez· Nov 27, 2024
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.

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