Math Essentials
jame581/GodotPrompter
A skill your agent uses when implementing game math — vectors, transforms, interpolation, curves, random number generation, and common geometric recipes
Guides essential mathematics for competitive programming including number theory, combinatorics, computational geometry, modular arithmetic, and probability Use when the user asks about math for…
$ npx skills add FerroxLabs/wayland --skill math-for-programming -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install FerroxLabs/wayland math-for-programming --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/FerroxLabs/wayland.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming .claude/skills/math-for-programming && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "math-for-programming" agent skill from https://github.com/FerroxLabs/wayland/tree/main/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming into .claude/skills/math-for-programming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "math-for-programming", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/FerroxLabs/wayland/tree/main/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programmingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add FerroxLabs/wayland --skill math-for-programming -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install FerroxLabs/wayland math-for-programming --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FerroxLabs/wayland.git skills-src && mkdir -p .agents/skills && cp -r skills-src/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming .agents/skills/math-for-programming && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "math-for-programming" agent skill from https://github.com/FerroxLabs/wayland/tree/main/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming into .agents/skills/math-for-programming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "math-for-programming", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add FerroxLabs/wayland --skill math-for-programming -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install FerroxLabs/wayland math-for-programming --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FerroxLabs/wayland.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming .cursor/skills/math-for-programming && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "math-for-programming" agent skill from https://github.com/FerroxLabs/wayland/tree/main/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming into .cursor/skills/math-for-programming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "math-for-programming", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/FerroxLabs/wayland.git --path src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add FerroxLabs/wayland --skill math-for-programming -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install FerroxLabs/wayland math-for-programming --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FerroxLabs/wayland.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming .gemini/skills/math-for-programming && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "math-for-programming" agent skill from https://github.com/FerroxLabs/wayland/tree/main/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming into .gemini/skills/math-for-programming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "math-for-programming", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install FerroxLabs/wayland math-for-programmingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add FerroxLabs/wayland --skill math-for-programming -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/FerroxLabs/wayland.git skills-src && mkdir -p .github/skills && cp -r skills-src/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming .github/skills/math-for-programming && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "math-for-programming" agent skill from https://github.com/FerroxLabs/wayland/tree/main/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming into .github/skills/math-for-programming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "math-for-programming", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add FerroxLabs/wayland --skill math-for-programming -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install FerroxLabs/wayland math-for-programming --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/FerroxLabs/wayland.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming .opencode/skills/math-for-programming && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "math-for-programming" agent skill from https://github.com/FerroxLabs/wayland/tree/main/src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming into .opencode/skills/math-for-programming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "math-for-programming", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
math-for-programmingGuides essential mathematics for competitive programming including number theory, combinatorics, computational geometry, modular arithmetic, and probability Use when the user asks about math for…
Math For Programming is an agent skill from FerroxLabs/wayland. Guides essential mathematics for competitive programming including number theory, combinatorics, computational geometry, modular arithmetic, and probability Use when the user asks about math for programming, related techniques, best practices, or needs guidance in this domain. Do NOT use when the request is outside the scope of math for programming or requires a different specialized skill.
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Wayland - The AI Agent That Perceives. Reasons. Acts. Evolves. The licence is Apache-2.0.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 4c030c7. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are cpp and template).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Math For Programming loads about 3.5k tokens when it runs. Until then it costs about 104 tokens; SKILL.md has 524 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from FerroxLabs/wayland at commit 4c030c7, republished under its Apache-2.0 licence (© FerroxLabs). 524 words, ~3,526 tokens.
.claude/skills/math-for-programming/SKILL.md (or your agent's skills folder).You are an expert competitive programming math coach. You guide programmers through the essential mathematical foundations needed for contests: number theory, modular arithmetic, combinatorics, computational geometry, probability, and linear algebra, with efficient implementations and proofs of correctness.
Use this skill when:
Do NOT use when:
const int MOD = 1e9 + 7;
long long mod(long long x) {
return ((x % MOD) + MOD) % MOD; // Handle negative
}
long long add(long long a, long long b) {
return (a + b) % MOD;
}
long long sub(long long a, long long b) {
return ((a - b) % MOD + MOD) % MOD;
}
long long mul(long long a, long long b) {
return (a % MOD) * (b % MOD) % MOD;
}// a^b mod m using binary exponentiation
// Time: O(log b)
long long power(long long a, long long b, long long m = MOD) {
long long result = 1;
a %= m;
while (b > 0) {
if (b & 1) result = result * a % m;
a = a * a % m;
b >>= 1;
}
return result;
}// Modular inverse using Fermat's little theorem (p must be prime)
// a^(-1) = a^(p-2) mod p
// Time: O(log p)
long long modInverse(long long a, long long p = MOD) {
return power(a, p - 2, p);
}
// Modular division: a / b mod p
long long modDiv(long long a, long long b, long long p = MOD) {
return mul(a, modInverse(b, p));
}
// Extended Euclidean Algorithm (works for non-prime modulus)
// Returns gcd(a, b), and sets x, y such that a*x + b*y = gcd(a, b)
long long extgcd(long long a, long long b, long long &x, long long &y) {
if (b == 0) {
x = 1; y = 0;
return a;
}
long long x1, y1;
long long g = extgcd(b, a % b, x1, y1);
x = y1;
y = x1 - (a / b) * y1;
return g;
}// Find all primes up to n
// Time: O(n log log n), Space: O(n)
vector<bool> sieve(int n) {
vector<bool> is_prime(n + 1, true);
is_prime[0] = is_prime[1] = false;
for (int i = 2; (long long)i * i <= n; i++) {
if (is_prime[i]) {
for (int j = i * i; j <= n; j += i)
is_prime[j] = false;
}
}
return is_prime;
}
// Linear sieve: also finds smallest prime factor
// Time: O(n), Space: O(n)
vector<int> linearSieve(int n) {
vector<int> spf(n + 1, 0); // smallest prime factor
vector<int> primes;
for (int i = 2; i <= n; i++) {
if (spf[i] == 0) {
spf[i] = i;
primes.push_back(i);
}
for (int p : primes) {
if (p > spf[i] || (long long)i * p > n) break;
spf[i * p] = p;
}
}
return spf;
}// Factorize n into prime factors
// Time: O(sqrt(n))
map<int, int> factorize(int n) {
map<int, int> factors;
for (int d = 2; (long long)d * d <= n; d++) {
while (n % d == 0) {
factors[d]++;
n /= d;
}
}
if (n > 1) factors[n]++;
return factors;
}
// Factorize using precomputed SPF (smallest prime factor)
// Time: O(log n) per factorization
map<int, int> factorizeSPF(int n, vector<int>& spf) {
map<int, int> factors;
while (n > 1) {
factors[spf[n]]++;
n /= spf[n];
}
return factors;
}// GCD using built-in
long long gcd(long long a, long long b) {
return __gcd(a, b); // Or use std::gcd in C++17
}
long long lcm(long long a, long long b) {
return a / gcd(a, b) * b; // Divide first to prevent overflow
}// phi(n) = count of integers in [1,n] coprime to n
// Time: O(sqrt(n))
int eulerTotient(int n) {
int result = n;
for (int p = 2; (long long)p * p <= n; p++) {
if (n % p == 0) {
while (n % p == 0) n /= p;
result -= result / p;
}
}
if (n > 1) result -= result / n;
return result;
}
// Sieve for all totient values up to n
// Time: O(n log log n)
vector<int> totientSieve(int n) {
vector<int> phi(n + 1);
iota(phi.begin(), phi.end(), 0);
for (int i = 2; i <= n; i++) {
if (phi[i] == i) { // i is prime
for (int j = i; j <= n; j += i)
phi[j] -= phi[j] / i;
}
}
return phi;
}// Precompute factorials for fast nCr
// Build: O(n), Query: O(1)
const int MAXN = 2e5 + 5;
long long fact[MAXN], inv_fact[MAXN];
void precompute_factorials() {
fact[0] = 1;
for (int i = 1; i < MAXN; i++)
fact[i] = fact[i-1] * i % MOD;
inv_fact[MAXN-1] = power(fact[MAXN-1], MOD - 2);
for (int i = MAXN - 2; i >= 0; i--)
inv_fact[i] = inv_fact[i+1] * (i+1) % MOD;
}
long long nCr(int n, int r) {
if (r < 0 || r > n) return 0;
return fact[n] % MOD * inv_fact[r] % MOD * inv_fact[n-r] % MOD;
}
long long nPr(int n, int r) {
if (r < 0 || r > n) return 0;
return fact[n] % MOD * inv_fact[n-r] % MOD;
}Key identities:
C(n, r) = C(n, n-r) (Symmetry)
C(n, r) = C(n-1, r-1) + C(n-1, r) (Pascal's rule)
C(n, 0) + C(n, 1) + ... + C(n, n) = 2^n
C(n+1, r+1) = sum_{i=r}^{n} C(i, r) (Hockey stick)
Catalan numbers: C_n = C(2n, n) / (n+1)
- Valid parenthesizations
- Binary trees with n nodes
- Monotonic lattice paths
Stars and bars: Ways to put n indistinguishable balls
in k distinguishable boxes = C(n+k-1, k-1)
Inclusion-Exclusion:
|A1 ∪ A2 ∪ ... ∪ An| = Σ|Ai| - Σ|Ai∩Aj| + Σ|Ai∩Aj∩Ak| - ...// D(n) = number of permutations with no fixed points
// D(n) = (n-1) * (D(n-1) + D(n-2))
// Time: O(n)
long long derangements(int n) {
if (n == 0) return 1;
if (n == 1) return 0;
vector<long long> d(n + 1);
d[0] = 1; d[1] = 0;
for (int i = 2; i <= n; i++)
d[i] = (i - 1) * (d[i-1] + d[i-2]) % MOD;
return d[n];
}using ld = long double;
const ld EPS = 1e-9;
struct Point {
ld x, y;
Point(ld x = 0, ld y = 0) : x(x), y(y) {}
Point operator+(const Point& p) const { return {x + p.x, y + p.y}; }
Point operator-(const Point& p) const { return {x - p.x, y - p.y}; }
Point operator*(ld t) const { return {x * t, y * t}; }
ld dot(const Point& p) const { return x * p.x + y * p.y; }
ld cross(const Point& p) const { return x * p.y - y * p.x; }
ld norm() const { return sqrt(x*x + y*y); }
ld norm2() const { return x*x + y*y; }
bool operator<(const Point& p) const {
if (abs(x - p.x) > EPS) return x < p.x;
return y < p.y;
}
};
// Cross product of vectors OA and OB (positive = counterclockwise)
ld cross(Point O, Point A, Point B) {
return (A - O).cross(B - O);
}
// Distance from point P to line through A and B
ld pointToLine(Point P, Point A, Point B) {
return abs(cross(A, B, P)) / (B - A).norm();
}
// Distance from point P to segment AB
ld pointToSegment(Point P, Point A, Point B) {
if ((B - A).dot(P - A) < EPS) return (P - A).norm();
if ((A - B).dot(P - B) < EPS) return (P - B).norm();
return pointToLine(P, A, B);
}// Andrew's monotone chain algorithm
// Time: O(n log n), Space: O(n)
vector<Point> convexHull(vector<Point> pts) {
int n = pts.size();
if (n < 3) return pts;
sort(pts.begin(), pts.end());
vector<Point> hull;
// Lower hull
for (auto& p : pts) {
while (hull.size() >= 2 &&
cross(hull[hull.size()-2], hull[hull.size()-1], p) <= 0)
hull.pop_back();
hull.push_back(p);
}
// Upper hull
int lower_size = hull.size();
for (int i = n - 2; i >= 0; i--) {
while ((int)hull.size() > lower_size &&
cross(hull[hull.size()-2], hull[hull.size()-1], pts[i]) <= 0)
hull.pop_back();
hull.push_back(pts[i]);
}
hull.pop_back(); // Remove duplicate of first point
return hull;
}// Signed area of polygon (positive if counterclockwise)
// Time: O(n)
ld polygonArea(vector<Point>& pts) {
ld area = 0;
int n = pts.size();
for (int i = 0; i < n; i++) {
int j = (i + 1) % n;
area += pts[i].cross(pts[j]);
}
return area / 2.0;
}// Matrix multiplication mod p
// Time: O(n^3) per multiplication, O(n^3 log k) for power
using Matrix = vector<vector<long long>>;
Matrix matmul(const Matrix& A, const Matrix& B) {
int n = A.size();
Matrix C(n, vector<long long>(n, 0));
for (int i = 0; i < n; i++)
for (int k = 0; k < n; k++)
if (A[i][k])
for (int j = 0; j < n; j++)
C[i][j] = (C[i][j] + A[i][k] * B[k][j]) % MOD;
return C;
}
Matrix matpow(Matrix A, long long p) {
int n = A.size();
Matrix result(n, vector<long long>(n, 0));
for (int i = 0; i < n; i++) result[i][i] = 1; // Identity
while (p > 0) {
if (p & 1) result = matmul(result, A);
A = matmul(A, A);
p >>= 1;
}
return result;
}
// Example: Fibonacci in O(log n)
long long fibonacci(long long n) {
if (n <= 1) return n;
Matrix M = {{1, 1}, {1, 0}};
Matrix result = matpow(M, n - 1);
return result[0][0];
}E[X + Y] = E[X] + E[Y] (always, even if dependent)
Indicator variable trick:
E[count of events] = sum of P(each event)
Example: Expected number of fixed points in random permutation
E = sum_{i=1}^{n} P(pi(i) = i) = n * (1/n) = 1X = number of trials until first success (p = success probability)
E[X] = 1/p
Var[X] = (1-p) / p^2
Example: Expected coin flips to get heads = 1/0.5 = 2| Mistake | Impact | Fix |
|---|---|---|
| Overflow in a * b % MOD | Wrong answer | Cast to long long before multiply |
| Not handling negative modulo | Wrong answer | Use ((x % MOD) + MOD) % MOD |
| Wrong inverse for composite modulus | Wrong answer | Use extended GCD, not Fermat |
| Floating point comparison | Unstable results | Use integer geometry when possible |
| Factorial overflow | Wrong answer | Precompute mod factorials |
| Off-by-one in nCr | Wrong answer | Check r <= n and r >= 0 |
| Division before multiplication | Precision loss (integers) | Multiply first, divide last |
| skipping modular inverse for division | Wrong answer | Never use / for modular division |
## Math For Programming Analysis
### Assessment
[Key findings and observations]
### Recommendations
1. [Primary recommendation]
2. [Secondary recommendation]
3. [Additional suggestions]
### Action Items
- [ ] [First action step]
- [ ] [Second action step]
- [ ] [Follow-up task]Input: "Help me with math for programming for my current situation"
Output:
Based on your situation, here is a structured approach to math for programming:
© FerroxLabs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming of FerroxLabs/wayland.
Open the folder on GitHubat commit 4c030c7
Math For Programming next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Math For Programming this skillFerroxLabs/wayland | 608 | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Math Essentialsjame581/GodotPrompter | 792 | — | ~3.3k | Automated safety check: Pass | MIT | |
| Mathparcadei/Continuous-Claude-v3 | 3.9k | 3 repos | ~1.6k | Automated safety check: Notes | MIT | |
| Math Olympiadanthropics/claude-plugins-official | 37k | — | ~5k | Automated safety check: Pass | Apache-2.0 | |
| Prime Numbersparcadei/Continuous-Claude-v3 | 3.9k | 1 repos | ~405 | Automated safety check: Notes | MIT | |
| Math Modeling Competition WorkflowXiaoMaColtAI/math-modeling-skill | 1.9k | — | ~1.2k | Automated safety check: Pass | None |
jame581/GodotPrompter
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parcadei/Continuous-Claude-v3
Unified math capabilities - computation, solving, and explanation.
anthropics/claude-plugins-official
Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses.
parcadei/Continuous-Claude-v3
Problem-solving strategies for prime numbers in graph number theory
XiaoMaColtAI/math-modeling-skill
Three-role workflow for math modeling contests: problem analysis, code and results, then a paper, with independent subagent checks at each stage gate.
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Runs reproducible math computations and counterexample searches with SymPy, NumPy and mpmath, logging evidence without presenting results as proofs.
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Guides essential mathematics for competitive programming including number theory, combinatorics, computational geometry, modular arithmetic, and probability Use when the user asks about math for…. Math For Programming is an agent skill from FerroxLabs/wayland. Guides essential mathematics for competitive programming including number theory, combinatorics, computational geometry, modular arithmetic, and probability Use when the user asks about math for programming, related techniques, best practices, or needs guidance in this domain.
Math For Programming fits situations like: the user asks about math for programming; related techniques; needs guidance in this domain; the request is outside the scope of math for programming.
Run `npx skills add FerroxLabs/wayland --skill math-for-programming -a claude-code`. Or copy the skill folder (src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming in FerroxLabs/wayland) into .claude/skills/math-for-programming in your project. Claude Code loads it when a task matches its description.
Run `npx skills add FerroxLabs/wayland --skill math-for-programming -a codex`. Or copy the skill folder (src/process/resources/skills-library/bodies/skills/emerging-tech/math-for-programming in FerroxLabs/wayland) into .agents/skills/math-for-programming in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add FerroxLabs/wayland --skill math-for-programming -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/math-for-programming, .gemini/skills/math-for-programming, .github/skills/math-for-programming and .opencode/skills/math-for-programming in your project.
SKILL.md names no scripts, command-line tools or credentials: Math For Programming is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Math For Programming is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Math For Programming: Math Essentials (jame581/GodotPrompter, 792 stars), Math (parcadei/Continuous-Claude-v3, 3.9k stars), Math Olympiad (anthropics/claude-plugins-official, 37k stars) and Prime Numbers (parcadei/Continuous-Claude-v3, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
FerroxLabs (a GitHub user) maintains it in FerroxLabs/wayland, which has 608 GitHub stars. The repository holds 1,194 skills in this directory. The repository was last updated on October 6, 2026.
Source: FerroxLabs/wayland on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.