mathguard - Selects math-heavy algorithms with explicit bounds and safeguards
Guides selection of named mathematical and approximate algorithms with explicit error, asymptotic, trade-off, and disqualifier analysis.
Tags
Updated: 2026-10-05Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Assess the classical algorithmic floor
- Identify named mathematical techniques
- Declare exact or approximate mode
- Specify error parameters
- Justify asymptotic bounds
- State optimization trade-offs
- Reject unsafe approximations
- Provide code or pseudocode
Inputs
- Problem and workload description
- Dataset scale
- Correctness requirements
- Performance constraints
- Caller error tolerance
- Existing code or algorithm context
- Team maintenance familiarity
Outputs
- Algorithm selection analysis
- Exactness and error statement
- Asymptotic bound justification
- Trade-off and disqualifier analysis
- Code or pseudocode
Requirements
- Prior lemmaly assessment that classical methods are insufficient