{"uid":"cap_qfla1GYdwxOJ8sFPG0dFh","slug":"agent-dojo-spar-runner-8ce3d9fa","name":"Agent-Dojo SPAR Runner","description":"AgentDojo SPAR endpoint: score your LLM agent's security against prompt-injection attacks. Submit an agent trace and get SPAR (Security, Privacy, Attack-Resistance) scores plus pass/fail on injected-goal detection. x402 pay-per-call on Base USDC. For red-teamers, AI-safety labs, and agents self-evaluating robustness to adversarial prompts.","url":"https://apiwitchcraft.duckdns.org/agent-dojo/spar","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"agentLogic":{"type":"object"},"scenarioId":{"type":"string"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.001","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":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_PtHGDhWbCaQu03viYBYgN","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs a SPAR (agent scenario) in the Agent-Dojo framework, executing a defined agent logic against a chosen scenario for robustness testing.","exampleAgentPrompt":"Run a SPAR simulation in Agent-Dojo using scenario ID 'phishing-resistance-01' with my agent logic defined as the provided strategy object — I want to see how it performs.","exampleUseCases":null,"resultDescription":"Returns the outcome of the agent scenario run, including performance metrics, agent decisions taken during the scenario, and any robustness or failure signals produced by the SPAR framework.","failureModes":["Invalid or unknown scenarioId returns an error","Malformed agentLogic object causes a schema validation failure","Payment failure (x402) if USDC balance is insufficient","Scenario execution timeout if agent logic produces infinite loops","Service unavailable if the duckdns host is unreachable"],"whenToPreferThis":"Choose this endpoint when you need to evaluate AI agent behavior against structured benchmark scenarios using the Agent-Dojo SPAR framework, particularly for robustness and adversarial testing. Prefer it over generic simulation tools when you have a specific scenarioId and agent logic object ready.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T00:34:18.176Z","isFirstParty":false}