Best use case
prime-sieve-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Generate optimized prime sieves and factorization routines
Teams using prime-sieve-generator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/prime-sieve-generator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How prime-sieve-generator Compares
| Feature / Agent | prime-sieve-generator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate optimized prime sieves and factorization routines
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Prime Sieve Generator Skill
## Purpose
Generate optimized prime sieves and factorization routines for various competitive programming scenarios.
## Capabilities
- Sieve of Eratosthenes (segmented, linear)
- Smallest prime factor sieve
- Miller-Rabin primality testing
- Pollard's rho factorization
- Precompute prime-related values
- Generate primes in range
## Target Processes
- prime-algorithms
- number-theory-algorithms
- combinatorics-counting
## Sieve Variants
### Basic Sieves
- Sieve of Eratosthenes O(n log log n)
- Linear sieve O(n)
- Segmented sieve (for large ranges)
### Factorization Sieves
- Smallest prime factor (SPF) sieve
- Mobius function sieve
- Euler's totient sieve
### Primality Testing
- Miller-Rabin (deterministic for small n)
- Fermat test
- Trial division
### Factorization
- Trial division O(sqrt(n))
- Pollard's rho O(n^1/4)
- Using SPF sieve O(log n)
## Input Schema
```json
{
"type": "object",
"properties": {
"type": {
"type": "string",
"enum": ["sieve", "primalityTest", "factorization", "spfSieve"]
},
"limit": { "type": "integer" },
"optimizations": { "type": "array" },
"language": {
"type": "string",
"enum": ["cpp", "python", "java"]
}
},
"required": ["type"]
}
```
## Output Schema
```json
{
"type": "object",
"properties": {
"success": { "type": "boolean" },
"code": { "type": "string" },
"complexity": { "type": "object" },
"memoryUsage": { "type": "string" }
},
"required": ["success", "code"]
}
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