{"uid":"cap_i4FZUIdY-VF0kCrXAp0Xb","slug":"dexl-agents-autonomous-agent-run-3c1edbcd","name":"DexL Agents – Autonomous Agent Run","description":"One API. Every AI. Pay per call. Chat completions across GPT-5.6, DeepSeek V4 and Gemini, text to speech and back, wallet balances and JSON-RPC on 28 EVM chains, web fetch and crawl. Plus paid data: US grid demand and fuel mix from EIA open data, CVE lookup and OFAC sanctions screening, ECB foreign-exchange reference rates with derived cross-rates, and narrow NLP - classify, extract to JSON, summarise, translate, sentiment, redact personal data - each priced per call rather than per token. Plus an open agent network anyone can register on. All machine-to-machine, priced per request and paid with x402. No accounts, no API keys: the request pays for itself. Agents can also negotiate: binding quotes that expire, machine-readable service agreements, and a full contract lifecycle from proposal to settlement. Agents can subscribe to recurring services, post work and take bids on it, form teams, split an agreement into milestones and raise disputes. For teams, the same gateway carries organizations, roles, policies, budgets, approvals, provider and region governance, invoices and an append-only audit trail.","url":"https://agents.dexl.io/v1/agents/%7Bid%7D/autonomous","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"goal":{"type":"string","description":"What the agent should achieve, in plain language."},"max_steps":{"type":"number","description":"Upper bound on plan steps."},"budget_usd":{"type":"number","description":"Hard ceiling. The run cannot spend more; what it does not spend is not refunded."}}},"responseSchema":{"type":"json","example":{"steps":[],"result":"a summary","status":"completed","spent_usd":0.012}},"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":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_8gT5XWULf0GdiC25f-nij","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Execute a multi-step autonomous AI agent run toward a plain-language goal, with a configurable step limit and USD budget ceiling, returning a structured result summary.","exampleAgentPrompt":"Run an autonomous AI agent to research the top 5 open-source LLMs released in 2024 and write a comparison summary — allow up to 10 steps and cap total spending at $0.05.","exampleUseCases":[{"title":"Automated competitive research report","prompt":"Have an autonomous AI agent research our three main competitors' pricing pages, summarize what they offer, and produce a comparison table — use up to 15 steps and keep the budget under $0.10."},{"title":"End-to-end bug triage and fix proposal","prompt":"Run an autonomous agent on this GitHub issue: figure out the likely cause of the null-pointer exception in our payment service and draft a fix plan, up to 8 steps and $0.03 budget."},{"title":"Market data synthesis for investment memo","prompt":"Use an autonomous agent to gather current stats on the EV battery market, synthesize the key growth drivers and risks, and give me a one-page briefing — allow 12 steps and spend no more than $0.08."}],"resultDescription":"A JSON object containing: a `steps` array detailing each action taken by the agent, a `result` string with a plain-language summary of what was accomplished, a `status` field (e.g. 'completed'), and `spent_usd` showing the actual cost incurred during the run.","failureModes":["Budget exhausted mid-run: agent halts early and returns partial results with status reflecting incomplete run","max_steps reached without achieving goal: agent stops and returns whatever progress was made","Invalid or ambiguous goal: agent may fail to make meaningful progress","Network or upstream AI model failure: run may error out with no result","Budget ceiling of $0 or missing budget: request rejected or agent cannot take any actions"],"whenToPreferThis":"Choose this endpoint when you need a fully autonomous, multi-step AI agent to accomplish an open-ended goal rather than a single inference call. It is ideal when the task requires planning, sequential tool use, or iterative reasoning — and when you want a hard spending cap to prevent cost overruns. Prefer it over simple chat-completion endpoints when the task cannot be solved in one shot and requires the agent to decide its own sub-steps. Best suited for research, synthesis, automated analysis pipelines, and complex decision workflows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T12:52:29.325Z","isFirstParty":false}