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Maha Strategies Exact Linear System Solver
x402
Maha Strategies Exact Linear System Solver is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.011/call, status unknown (last checked 2026-09-14).
Solves a 1-8 variable rational linear system exactly, returning rank, pivots, particular solution, and null space while classifying the system as unique, inconsistent, or underdetermined.
Price / call$0.011
Success—
StatusUnknown
How this service works
Get an inspectable exact solution to a 1-8 variable rational linear system. Returns rank, pivots, particular solution and null space; distinguishes unique, inconsistent and underdetermined systems. No floating-point conditioning or physical-model assessment.
Output
Returns a structured JSON result containing: the system rank, pivot column indices, a particular solution vector (if one exists), the null space basis vectors, and a classification of the system as unique (one solution), inconsistent (no solution), or underdetermined (infinitely many solutions). Also returns versioning, offer ID, input and receipt digests, and amount charged in base units.
Example use cases
Verify unique solution for 3×3 system
“I have a 3-variable system of equations: 2x + y = 5, x - y + z = 3, 3x + 2y - z = 7. Solve it exactly and confirm whether there's a unique solution, and if so, what it is.”
Classify underdetermined homework system
“Can you solve this underdetermined system exactly and give me the general solution with the null space? Matrix is [[1,2,3],[0,1,4]] and the right-hand side is [1,2].”
Check if system is inconsistent
“I need to know if this system of equations is inconsistent — matrix rows are [1,1,1], [2,2,2], [3,3,4] and the right-hand side is [6,12,10]. Run an exact solve and tell me the rank and whether a solution exists.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/micro/exact-linear-systemWhen to prefer
Choose this endpoint when you need an exact, symbolic-quality solution to a small (1-8 variable) rational linear system and cannot tolerate floating-point rounding errors. It is ideal for formal verification, educational or audit contexts, or any scenario where the distinction between unique, inconsistent, and underdetermined systems must be provably correct. Prefer alternatives if you need large-scale numerical solvers, physical model conditioning, or systems with more than 8 variables.
Side effects
- Matrix or RHS dimension mismatch — more than 8 rows or columns rejected
- Invalid data class enum value causes validation error
- Non-numeric or malformed matrix/RHS entries cause parse failure
- Empty matrix or RHS array (below minItems of 1) rejected
- Payment failure via x402 protocol prevents execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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