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Numora Matrix Rank Computation
x402
Numora Matrix Rank Computation is a paid API for AI agents from numormo.vercel.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-14).
Computes the rank of a given matrix (2D array) using pure mathematical computation with no external dependencies.
Price / call$0.1
Success—
StatusUnknown
How this service works
100 pure math computation endpoints for AI agents. Statistics, financial math, linear algebra, equation solving, calculus, number theory, sequence generation, and unit conversions. Zero external dependencies. x402 micropayments on Base.
Output
Returns a JSON object with 'success' (boolean), 'result' (object containing the computed rank value), and 'computation' (a human-readable string describing what was computed, e.g. 'Rank of a 3x3 matrix').
Example use cases
Check linear independence of vectors
“I have these three vectors represented as rows: [[1,0,2],[0,1,3],[1,1,5]] — can you tell me the rank of this matrix so I know if they're linearly independent?”
Verify system of equations solvability
“Before I try to solve this system of equations, can you compute the rank of the coefficient matrix [[2,1,-1],[4,5,2],[1,2,3]] so I know if the system has a unique solution?”
Dimensionality check for data matrix
“I have a 4x4 feature matrix [[1,2,0,1],[2,4,0,2],[0,1,1,0],[3,5,2,1]] — what's its rank so I can figure out the effective dimensionality of my data?”
Technical details
Endpoint
POSThttps://numormo.vercel.app/api/matrix/rankWhen to prefer
Choose this endpoint when you need a fast, self-contained, dependency-free matrix rank computation for linear algebra tasks such as checking linear independence, verifying solvability of linear systems, or analyzing data dimensionality. Ideal for AI agents that need precise mathematical results without relying on external math libraries or cloud ML services. Pay-per-call micropayment model suits on-demand, infrequent use cases.
Side effects
- Malformed or non-rectangular matrix input returns an error
- Non-numeric values in matrix elements cause computation failure
- Empty matrix or missing 'A' field returns validation error
- Extremely large matrices may time out or hit memory limits
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| Arequired | array | Matrix (2D array) |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| resultrequired | object | Computation result varies by endpoint |
| successrequired | boolean | Always true on success |
| computationrequired | string | Human-readable description of what was computed |
Tags
x402
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