{"uid":"cap_RWNJIZR3RIIm3Vfw8V_Sb","slug":"numora-matrix-trace-78be128b","name":"Numora Matrix Trace","description":"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.","url":"https://numormor.netlify.app/api/matrix/trace","method":"POST","headers":{},"bodySchema":{"type":"object","required":["A"],"properties":{"A":{"type":"array","description":"Matrix (2D array)"}}},"responseSchema":{"type":"object","required":["success","result","computation"],"properties":{"result":{"type":"object","description":"Computation result varies by endpoint"},"success":{"type":"boolean","description":"Always true on success"},"computation":{"type":"string","description":"Human-readable description of what was computed"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.1","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":{"p10Cents":"10.0000","medianCents":"10.0000","p90Cents":"10.0000","minCents":"10.0000","maxCents":"10.0000","p95Cents":"10.0000","sampleCount":1,"varies":false,"failureChargeRate":1},"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.1/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_ERsiW8M6nqP9i68tEkLq3","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.1","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes the trace (sum of diagonal elements) of a square matrix","exampleAgentPrompt":"Can you compute the trace of this matrix for me: [[3, 1, 2], [0, 5, 4], [7, 8, 9]]?","exampleUseCases":[{"title":"Portfolio covariance matrix analysis","prompt":"I need to find the trace of this correlation matrix to understand the total variance across my investment portfolio: [[1.0, 0.3, 0.2], [0.3, 1.0, 0.5], [0.2, 0.5, 1.0]]. What does that tell me?"},{"title":"Machine learning model layer verification","prompt":"Can you compute the trace of this weight matrix from my neural network layer to help me validate the model's numerical properties: [[0.5, -0.2, 0.1], [0.3, 0.8, -0.4], [-0.1, 0.6, 0.2]]?"},{"title":"System stability eigenvalue check","prompt":"I'm analyzing a dynamical system and need the trace of this state transition matrix to estimate the sum of eigenvalues: [[2, 1, 0], [0, 3, 1], [0, 0, 1]]. Can you calculate that for me?"}],"resultDescription":"Returns a JSON object with a boolean success flag, a result object containing the computed trace (scalar sum of the main diagonal), and a human-readable computation description string explaining what was calculated.","failureModes":["Non-square matrix provided — trace is undefined for non-square matrices","Missing required field A — returns validation error","A is not a 2D array — malformed input error","Empty matrix array — computation error","Payment not completed via x402 — 402 Payment Required response"],"whenToPreferThis":"Use this endpoint when you need a pure, dependency-free computation of the matrix trace (sum of diagonal elements) for any square matrix. Prefer this over general-purpose math libraries when you need a lightweight, API-accessible, pay-per-use computation in an agent workflow, especially when already using the Numora suite of math endpoints.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T06:34:10.467Z","isFirstParty":false}