Agent skill

Competitive Debugging Master

by FerroxLabs in FerroxLabs/wayland

Competitive programming debugging mastery covering stress testing with random test generators, systematic edge case identification, time and memory optimization techniques, common bug patterns in…

Apache-2.0Auto-check passedDevelopment

Install Competitive Debugging Master

skills CLI
$ npx skills add FerroxLabs/wayland --skill competitive-debugging-master -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install FerroxLabs/wayland competitive-debugging-master --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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/competitive-debugging-master .claude/skills/competitive-debugging-master && rm -rf skills-src

Use ~/.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/

Facts

Skill name
competitive-debugging-master
GitHub stars
608
Token cost
~4.2k tokens
SKILL.md length
442 words
Files
1
Skills in repo
1,194
Repo updated
First seen
Licence
Apache-2.0

At a glance

Competitive programming debugging mastery covering stress testing with random test generators, systematic edge case identification, time and memory optimization techniques, common bug patterns in…

  • Works in 5 steps: Problem and solution: Share both the… → Symptom: Wrong Answer, Time Limit… → Test cases: Does it pass the sample… → …
  • The user asks about competitive debugging master
  • SKILL.md covers When to Use, Questions to Ask the User First, Debugging Decision Tree and Stress Testing Framework, plus 9 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Competitive Debugging Master is an agent skill from FerroxLabs/wayland. Competitive programming debugging mastery covering stress testing with random test generators, systematic edge case identification, time and memory optimization techniques, common bug patterns in contest code, binary search on test cases, and strategies for debugging under contest time pressure. Use when the user asks about competitive debugging master, related techniques, best practices, or needs guidance in this domain. Do NOT use when the request is outside the scope of competitive debugging master or requires…

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Debugging, Load testing and Test generation. The repository describes itself as: Wayland - The AI Agent That Perceives. Reasons. Acts. Evolves. The licence is Apache-2.0.

When your agent uses it

  • The user asks about competitive debugging master
  • Related techniques
  • Needs guidance in this domain
  • The request is outside the scope of competitive debugging master

Example prompts

  • “/competitive-debugging-master”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Problem and solution: Share both the problem statement and your current code.
  2. Symptom: Wrong Answer, Time Limit Exceeded, Runtime Error, or Memory Limit Exceeded?
  3. Test cases: Does it pass the sample cases? Do you have a failing test case?
  4. Approach: Describe your algorithm -- I need to understand your intended logic.
  5. Contest context: Are you under time pressure, or is this practice?

What it can do on your machine

Read from SKILL.md and the folder at commit 4c030c7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are cpp, bash, python and template).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Competitive Debugging Master loads about 4.2k tokens when it runs. Until then it costs about 145 tokens; SKILL.md has 442 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~145
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from FerroxLabs/wayland at commit 4c030c7, republished under its Apache-2.0 licence (© FerroxLabs). 442 words, ~4,203 tokens.

Download SKILL.mdSave it as .claude/skills/competitive-debugging-master/SKILL.md (or your agent's skills folder).
name
competitive-debugging-master
description
Competitive programming debugging mastery covering stress testing with random test generators, systematic edge case identification, time and memory optimization techniques, common bug patterns in contest code, binary search on test cases, and strategies for debugging under contest time pressure. Use when the user asks about competitive debugging master, related techniques, best practices, or needs guidance in this domain. Do NOT use when the request is outside the scope of competitive debugging master or requires a different specialized skill.
license
Apache-2.0
metadata.author
foundry-skills
metadata.version
1.0.0
metadata.tags
advanced competitive-programming stress-management checklist template beginner-friendly python testing
metadata.category
emerging-tech
metadata.subcategory
competitive-programming
metadata.disclaimer
none
metadata.difficulty
advanced

Competitive Debugging Master

You are an expert competitive programmer specializing in debugging contest solutions. You systematically find bugs using stress testing, identify edge cases that break solutions, optimize code for tight time limits, and apply disciplined debugging strategies that work under contest pressure.

When to Use

Use this skill when:

  • User asks about competitive debugging master techniques or best practices
  • User needs guidance on competitive debugging master concepts
  • User wants to implement or improve their approach to competitive debugging master

Do NOT use when:

  • The request falls outside the scope of competitive debugging master
  • User needs a different specialized skill for their specific situation
  • The topic requires professional consultation beyond general guidance

Questions to Ask the User First

  1. Problem and solution: Share both the problem statement and your current code.
  2. Symptom: Wrong Answer, Time Limit Exceeded, Runtime Error, or Memory Limit Exceeded?
  3. Test cases: Does it pass the sample cases? Do you have a failing test case?
  4. Approach: Describe your algorithm -- I need to understand your intended logic.
  5. Contest context: Are you under time pressure, or is this practice?

Debugging Decision Tree

Symptom?
├── Wrong Answer (WA)
│   ├── Fails on samples? → Logic error, re-read problem statement
│   ├── Passes samples, fails on submit?
│   │   ├── Build stress test → Find smallest failing case
│   │   ├── Check edge cases (N=0, N=1, all same, max values)
│   │   └── Check integer overflow, off-by-one, array bounds
│   └── Passes most but not all?
│       └── Likely corner case or overflow on large inputs
│
├── Time Limit Exceeded (TLE)
│   ├── Wrong complexity? → Rethink algorithm
│   ├── Right complexity but slow constant? → Optimize I/O, data structures
│   └── Borderline? → Constant factor optimization (see section below)
│
├── Runtime Error (RE)
│   ├── Array out of bounds → Check array sizes, loop bounds
│   ├── Division by zero → Add guards
│   ├── Stack overflow → Increase stack or convert recursion to iteration
│   └── Null/invalid access → Check edge cases (empty input)
│
└── Memory Limit Exceeded (MLE)
    ├── Too many allocations → Use arrays instead of vectors/maps
    ├── Oversized array → Reduce dimensions or use sparse structure
    └── Recursion depth → Convert to iterative

Stress Testing Framework

The Gold Standard: Brute Force vs Optimized
cpp
// stress_test.cpp -- Find smallest failing test case
#include <bits/stdc++.h>
using namespace std;

// Your optimized solution
int solve(vector<int>& a) {
    // ... your algorithm ...
}

// Brute force (definitely correct, possibly slow)
int brute(vector<int>& a) {
    // ... O(N^2) or O(N^3) simple approach ...
}

// Random test generator
vector<int> generate(mt19937& rng, int maxN, int maxVal) {
    int n = rng() % maxN + 1;
    vector<int> a(n);
    for (int& x : a) x = rng() % (2 * maxVal + 1) - maxVal;
    return a;
}

int main() {
    mt19937 rng(42);  // fixed seed for reproducibility

    for (int test = 1; test <= 1000000; test++) {
        vector<int> a = generate(rng, 10, 100);  // small cases first

        int expected = brute(a);
        int actual = solve(a);

        if (expected != actual) {
            cout << "FAILED on test " << test << endl;
            cout << "Input: ";
            for (int x : a) cout << x << " ";
            cout << endl;
            cout << "Expected: " << expected << endl;
            cout << "Actual: " << actual << endl;
            return 1;
        }

        if (test % 10000 == 0) {
            cerr << "Passed " << test << " tests" << endl;
        }
    }
    cout << "All tests passed!" << endl;
}
shell Stress Test (Separate Files)
shell
#!shell-interpreter
# stress-test script - compare two solutions
g++ -O2 solve.cpp -o solve
g++ -O2 brute.cpp -o brute
g++ -O2 gen.cpp -o gen

for i in $(seq 1 10000); do
    ./gen $i > input.txt          # seed = test number
    ./solve < input.txt > out1.txt
    ./brute < input.txt > out2.txt
    if ! diff -q out1.txt out2.txt > ./dev/null 2>&1; then
        echo "MISMATCH on test $i"
        echo "Input:"
        cat input.txt
        echo "Expected:"
        cat out2.txt
        echo "Got:"
        cat out1.txt
        exit 1
    fi
done
echo "All tests passed!"
Random Test Generator Patterns
cpp
// gen.cpp - takes seed as command-line argument
#include <bits/stdc++.h>
using namespace std;

int main(int argc, char* argv[]) {
    mt19937 rng(atoi(argv[1]));

    // Array of integers
    int n = rng() % 10 + 1;
    cout << n << "\n";
    for (int i = 0; i < n; i++)
        cout << (rng() % 201 - 100) << " \n"[i == n-1];

    // Tree (random parent for each node)
    int n = rng() % 10 + 2;
    cout << n << "\n";
    for (int i = 2; i <= n; i++) {
        int parent = rng() % (i - 1) + 1;
        cout << parent << " " << i << "\n";
    }

    // Random permutation
    int n = rng() % 10 + 1;
    vector<int> perm(n);
    iota(perm.begin(), perm.end(), 1);
    shuffle(perm.begin(), perm.end(), rng);
    cout << n << "\n";
    for (int x : perm) cout << x << " ";
    cout << "\n";

    // Random graph (N nodes, M edges, no self-loops, no multi-edges)
    int n = rng() % 8 + 2, m = rng() % (n*(n-1)/2) + 1;
    set<pair<int,int>> edges;
    while ((int)edges.size() < m) {
        int u = rng() % n + 1, v = rng() % n + 1;
        if (u != v) edges.insert({min(u,v), max(u,v)});
    }
    cout << n << " " << m << "\n";
    for (auto [u,v] : edges) cout << u << " " << v << "\n";
}

Edge Case Checklist

Universal Edge Cases
□ N = 0 (empty input)
□ N = 1 (single element)
□ N = 2 (minimum for pairwise operations)
□ All elements identical
□ Already sorted (ascending)
□ Reverse sorted (descending)
□ Maximum values (1e9, 1e18)
□ Minimum values (negative, zero)
□ Negative numbers (if allowed)
□ Answer is zero
□ Answer requires 64-bit integer
Data Structure Specific
Arrays:
□ Single element array
□ Two elements (swap needed?)
□ All same values
□ Sorted / reverse sorted
□ Maximum size with extreme values

Trees:
□ Single node
□ Linear chain (degenerate tree, depth = N)
□ Star graph (one root, N-1 leaves)
□ Complete binary tree
□ Disconnected (if not guaranteed connected)

Graphs:
□ No edges (isolated nodes)
□ Complete graph
□ Single path
□ Self-loops (if allowed)
□ Disconnected components
□ Negative weight edges/cycles

Strings:
□ Empty string
□ Single character
□ All same character ("aaaa")
□ Palindrome
□ Maximum length
Numeric Edge Cases
Integer overflow checkpoints:
□ Multiplication of two 32-bit ints → need 64-bit (>2e9)
□ Sum of N values each up to 1e9, N up to 2e5 → need 64-bit (>2e14)
□ Square of distance (1e9 squared = 1e18, fits in long long)
□ Product of three values → may need __int128 or modular arithmetic

Modular arithmetic:
□ Subtraction can go negative: use (a - b + MOD) % MOD
□ Division requires modular inverse, not regular division
□ Intermediate products can overflow before mod: use (ll)a * b % MOD

Floating point:
□ Comparison: use eps = 1e-9, not ==
□ Large values lose precision: 1e15 + 1.0 == 1e15 in double
□ atan2(0, 0) is defined but may cause issues

Time Optimization Techniques

Input/Output Speed
cpp
// ALWAYS include these in competitive programming
ios::sync_with_stdio(false);
cin.tie(nullptr);

// For very large I/O (>1MB), use custom reader:
inline int readInt() {
    int x = 0, c = getchar_unlocked();
    bool neg = false;
    while (c < '0') { neg = (c == '-'); c = getchar_unlocked(); }
    while (c >= '0') { x = x * 10 + c - '0'; c = getchar_unlocked(); }
    return neg ? -x : x;
}

// Printf is faster than cout for formatted output
printf("%d\n", answer);  // faster than cout << answer << "\n";
Data Structure Optimizations
cpp
// Prefer array over vector when size is known
int a[200005];  // faster than vector<int> a(n)

// Prefer array over map/unordered_map
int cnt[1000005] = {};  // faster than map<int,int> .// Reserve vector capacity
vector<int> v;
v.reserve(n);  // avoid reallocations

// Use emplace_back instead of push_back for objects
v.emplace_back(x, y);  // construct in-place

// Sort comparison: pass by const reference
sort(a.begin(), a.end(), [](const auto& x, const auto& y) {
    return x.first < y.first;
});
Algorithm-Level Optimizations
cpp
// Binary search instead of linear search: O(N) → O(log N)
// Two pointers instead of nested loops: O(N^2) → O(N)
// Prefix sums instead of range queries: O(NQ) → O(N+Q)
// Sparse table instead of segment tree for static RMQ: lower constant

// Avoid unnecessary copies
for (const auto& x : vec) { ... }  // reference, not copy
// Not: for (auto x : vec) { ... } // copies each element

// Short-circuit evaluation
if (expensive_check && cheap_check) ...  // BAD
if (cheap_check && expensive_check) ...  // GOOD

// Bitset for boolean arrays (64x speedup for AND/OR/COUNT)
bitset<100005> visited;
// Instead of: bool visited[100005];
Constant Factor Tricks
cpp
// Cache-friendly access (iterate by rows, not columns)
// BAD: for (j) for (i) a[i][j]  -- cache miss every access
// GOOD: for (i) for (j) a[i][j]  -- sequential access

// __builtin functions (single CPU instruction)
__builtin_popcount(x);  // count bits
__builtin_clz(x);       // leading zeros (for log2)
__builtin_ctz(x);       // trailing zeros

// Pragmas for auto-vectorization (GCC)
#pragma GCC optimize("O2,unroll-loops")
#pragma GCC target("avx2,bmi,bmi2,popcnt")

Common Bug Patterns

The Bug Hall of Fame
cpp
// 1. Integer overflow
int n = 200000;
int result = n * n;  // OVERFLOW! 4e10 > INT_MAX
long long result = (long long)n * n;  // correct

// 2. Off-by-one in binary search
// Wrong: while (lo < hi) with hi = n (should be n-1, or use lo <= hi)
int lo = 0, hi = n - 1;
while (lo <= hi) {
    int mid = lo + (hi - lo) / 2;  // avoid overflow in (lo+hi)/2
    if (check(mid)) hi = mid - 1;
    else lo = mid + 1;
}

// 3. Uninitialized variables / arrays
memset(dp, -1, sizeof dp);  // initialize DP array
// Or: fill(dp, dp + n, -1);

// 4. Wrong modular arithmetic
int ans = (a - b) % MOD;      // can be negative!
int ans = ((a - b) % MOD + MOD) % MOD;  // correct

// 5. Array size too small
int a[100005];  // N up to 1e5? Use 1e5 + 5 for safety
// Common mistake: graph with M edges needs adj list of size N, not M

// 6. skipping to reset between test cases
int t; cin >> t;
while (t--) {
    // MUST reset all global state here
    fill(visited, visited + n + 1, false);
    for (int i = 0; i <= n; i++) adj[i].clear();
}

// 7. Wrong comparison in sort
// Must be strict weak ordering: never return true for equal elements
sort(a, a+n, [](int x, int y) { return x <= y; });  // WRONG (undefined behavior)
sort(a, a+n, [](int x, int y) { return x < y; });   // correct

Binary Search on Test Case Size

When you have a failing test case that's too large to debug:

1. Verify it actually fails: run and confirm WA/RE
2. Binary search on input size:
   - Take first N/2 elements → still fails? Recurse on smaller
   - Doesn't fail? Take first 3N/4 elements → ...
3. For structured input (trees, graphs):
   - Remove leaf nodes one at a time
   - Remove edges one at a time
   - Check if failure persists after each removal
4. Goal: find the SMALLEST input that triggers the bug
python
# Automated test case minimizer
import subprocess

def run_solution(input_data):
    result = subprocess.run(['./solve'], input=input_data,
                          capture_output=True, text=True, timeout=5)
    return result.stdout.strip()

def run_brute(input_data):
    result = subprocess.run(['./brute'], input=input_data,
                          capture_output=True, text=True, timeout=30)
    return result.stdout.strip()

def minimize(elements):
    """Binary search to find minimal failing subset."""
    if len(elements) <= 1:
        return elements

    mid = len(elements) // 2
    left = elements[:mid]
    right = elements[mid:]

    # Try just left half
    test_input = format_input(left)
    if run_solution(test_input) != run_brute(test_input):
        return minimize(left)

    # Try just right half
    test_input = format_input(right)
    if run_solution(test_input) != run_brute(test_input):
        return minimize(right)

    # Need elements from both halves -- try removing one at a time
    for i in range(len(elements)):
        reduced = elements[:i] + elements[i+1:]
        test_input = format_input(reduced)
        if run_solution(test_input) != run_brute(test_input):
            return minimize(reduced)

    return elements  # all elements needed

Debugging Under Time Pressure

The 5-Minute Rule
In a contest, if your solution gets WA:

Minute 0-1: Re-read the problem statement carefully
  - Did you misunderstand the output format?
  - Are there constraints you missed?
  - 1-indexed vs 0-indexed?

Minute 1-3: Check the obvious
  - Integer overflow (use long long everywhere if unsure)
  - Array bounds (add +5 to all array sizes)
  - Uninitialized variables
  - Multiple test cases: are you resetting state?

Minute 3-5: Run stress test
  - Write 30-second brute force
  - Write 30-second generator
  - Run 10,000 small cases
  - If mismatch found, print minimal failing case and debug

If no bug found in 5 minutes: MOVE TO ANOTHER PROBLEM
Come back with fresh eyes later.
Pre-Contest Debugging Template
cpp
// template.cpp -- compile with: g++ -O2 -Wall -Wextra -DLOCAL
#include <bits/stdc++.h>
using namespace std;

#ifdef LOCAL
#define dbg(x) cerr << #x << " = " << (x) << endl
#define dbgv(v) { cerr << #v << " = ["; for(auto& x:v) cerr << x << ","; cerr << "]" << endl; }
#else
#define dbg(x)
#define dbgv(v)
#endif

int main() {
    ios::sync_with_stdio(false);
    cin.tie(nullptr);

    // Solution here
    // Use dbg(variable) freely -- stripped in submission

    return 0;
}
Show full SKILL.md (187 more words)Show less

Process

  1. Gather information. Ask the user clarifying questions to understand their specific situation, goals, and constraints
  2. Analyze context. Review the information provided and identify key factors relevant to competitive debugging master
  3. Develop recommendations. Apply domain expertise to create actionable guidance tailored to the user's needs
  4. Present structured output. Deliver findings in the output format below with clear next steps
  5. Address follow-ups. Answer additional questions and refine recommendations based on feedback

Output Format

template
## Competitive Debugging Master 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]

Edge Cases

  • Incomplete information: Ask clarifying questions before proceeding with recommendations
  • Conflicting requirements: Prioritize the most critical constraint and note trade-offs
  • Out of scope requests: Redirect to appropriate specialized skill or professional resource
  • Beginner vs advanced: Adjust depth and terminology based on user's experience level

Example

Input: "Help me with competitive debugging master for my current situation"

Output:

Based on your situation, here is a structured approach to competitive debugging master:

  1. Assessment: Evaluate your current state and identify key areas for improvement
  2. Strategy: Develop a targeted plan based on best practices
  3. Implementation: Execute the plan with specific, measurable steps
  4. Review: Monitor progress and adjust as needed

© 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

Files

Just SKILL.md in src/process/resources/skills-library/bodies/skills/emerging-tech/competitive-debugging-master of FerroxLabs/wayland.

Open the folder on GitHubat commit 4c030c7

Compare with similar skills

Competitive Debugging Master 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.

Competitive Debugging Master compared with similar skills
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State Snapshot InstrumenterArabelaTso/Skills-4-SE253—~2.2kAutomated safety check: PassApache-2.0
Feature ContractFastLED/FastLED7.5k—~1.7kAutomated safety check: PassMIT
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Code Repair Generation ComboArabelaTso/Skills-4-SE253—~1.3kAutomated safety check: PassApache-2.0

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Questions about Competitive Debugging Master

What does Competitive Debugging Master do?

Competitive programming debugging mastery covering stress testing with random test generators, systematic edge case identification, time and memory optimization techniques, common bug patterns in…. Competitive Debugging Master is an agent skill from FerroxLabs/wayland. Competitive programming debugging mastery covering stress testing with random test generators, systematic edge case identification, time and memory optimization techniques, common bug patterns in contest code, binary search on test cases, and strategies for debugging under contest time pressure.

When should I use Competitive Debugging Master?

Competitive Debugging Master fits situations like: the user asks about competitive debugging master; related techniques; needs guidance in this domain; the request is outside the scope of competitive debugging master.

How do I install Competitive Debugging Master in Claude Code?

Run `npx skills add FerroxLabs/wayland --skill competitive-debugging-master -a claude-code`. Or copy the skill folder (src/process/resources/skills-library/bodies/skills/emerging-tech/competitive-debugging-master in FerroxLabs/wayland) into .claude/skills/competitive-debugging-master in your project. Claude Code loads it when a task matches its description.

How do I install Competitive Debugging Master in Codex?

Run `npx skills add FerroxLabs/wayland --skill competitive-debugging-master -a codex`. Or copy the skill folder (src/process/resources/skills-library/bodies/skills/emerging-tech/competitive-debugging-master in FerroxLabs/wayland) into .agents/skills/competitive-debugging-master in your project. Codex loads it when a task matches its description.

Can I use Competitive Debugging Master in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add FerroxLabs/wayland --skill competitive-debugging-master -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/competitive-debugging-master, .gemini/skills/competitive-debugging-master, .github/skills/competitive-debugging-master and .opencode/skills/competitive-debugging-master in your project.

What does Competitive Debugging Master need to run?

SKILL.md names no scripts, command-line tools or credentials: Competitive Debugging Master is instructions for the agent only. Our summary lists: Python 3.

Does Competitive Debugging Master access the network?

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.

Is Competitive Debugging Master safe to install?

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.

What licence does Competitive Debugging Master use?

Competitive Debugging Master 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.

How many tokens does Competitive Debugging Master use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Competitive Debugging Master?

Skills that share tags, products or a category with Competitive Debugging Master: OpenROAD Bug Fixer (The-OpenROAD-Project/OpenROAD, 3.2k stars), State Snapshot Instrumenter (ArabelaTso/Skills-4-SE, 253 stars), Feature Contract (FastLED/FastLED, 7.5k stars) and Dev (npc-live/clawfirm, 156 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Competitive Debugging Master?

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.