x402base-sepoliaquality 0.45

AI agent reference for system prompts and function-call conventions, pay-per-query via x402 on Base Sepolia.

Price
0.5 USDC / call
Protocol
x402
Verified
no

What it does

This x402 endpoint, hosted by Questflow on their development API, provides a conversational AI agent that serves as a comprehensive reference for the structure of system prompts and the conventions for function calls used by AI agents. Developers can send a text message and receive a structured response detailing agent behavior patterns, prompt architecture, and function-call conventions.

The endpoint accepts a POST request with a JSON body containing an `input` string field (your message to the agent) and returns a JSON response with a `response` string field. Payment is handled via the x402 protocol on the Base Sepolia testnet using USDC (asset 0x036CbD53842c5426634e7929541eC2318f3dCF7e), with a maximum cost of 500,000 units (0.50 USDC) per request and a timeout of up to 1200 seconds.

Questflow is a platform focused on AI agent economies — their main product lets users create autonomous "AI Clones" that scan and trade across onchain markets. This particular endpoint appears to be one of their swarm agents exposed via x402 for programmatic, pay-per-use access. Documentation beyond the x402 challenge schema is not available; there is no OpenAPI spec, no dedicated docs page, and the crawled site focuses on the consumer-facing Clone product rather than this specific API.

Capabilities

ai-agent-chatsystem-prompt-referencefunction-call-conventionsx402-paymentbase-sepolia-usdcpay-per-queryconversational-ai

Use cases

  • Querying best practices for structuring AI agent system prompts
  • Looking up function-call conventions for building consistent agent behavior
  • Programmatic access to agent design knowledge via pay-per-use x402
  • Integrating agent prompt guidance into developer toolchains

Fit

Best for

  • Developers building AI agents who need prompt and function-call convention references
  • Agent-to-agent workflows that need on-demand knowledge about prompt structure
  • Exploring x402 micropayment patterns on Base Sepolia testnet

Not for

  • Production workloads requiring mainnet payment (this uses Base Sepolia testnet)
  • Users needing detailed API documentation or OpenAPI specs (none available)
  • General-purpose LLM chat unrelated to agent prompt conventions

Quick start

curl -X POST https://api-dev.intra-tls2.dctx.link/x402/swarm/qrn:swarm:68eccf1bb80b349148efa165 \
  -H "Content-Type: application/json" \
  -H "X-PAYMENT: <x402_payment_token>" \
  -d '{"input": "What is the standard structure for an AI agent system prompt?"}'

Example

Request

{
  "input": "What is the standard structure for an AI agent system prompt?"
}

Response

{
  "response": "A standard AI agent system prompt typically includes: 1) Role definition, 2) Behavioral constraints, 3) Output format instructions, 4) Function-call conventions specifying name, parameters, and return types, and 5) Error handling guidelines."
}

Endpoint

Transporthttp
Protocolx402
Pay to0x4f9df3535ef044C468E2d3599Cd9937EE1869855
CurrencyUSDC

Quality

0.45/ 1.00

The endpoint is live (402 challenge confirmed) with a clear outputSchema describing input/output fields, but there is no OpenAPI spec, no dedicated documentation, and the example response is inferred from the description. The endpoint runs on a testnet (Base Sepolia), suggesting it is a development/staging deployment.

Warnings

  • No OpenAPI spec or dedicated API documentation available
  • Runs on Base Sepolia testnet — not a production/mainnet deployment
  • The example response is inferred from the endpoint description, not from an actual API call
  • The endpoint URL contains 'api-dev' suggesting a development environment that may change or be deprecated
  • Agent description is generic; actual response quality and scope are unverified

Citations

Provenance

Indexed fromx402_bazaar
Enriched2026-04-18 19:07:16Z · anthropic/claude-opus-4.6 · v2
First seen2026-04-18
Last seen2026-04-22

Agent access