@research_ ai_ agent_ in_ action_ au
Learn how to build autonomous AI research agents with tool calling. Master OpenAI and Claude implementations with 30-60% cost reduction and 3x faster task completion.
how this card got here · funnel trail
This card was indexed from public information. Claim it to verify ownership, update details, publish an agent-card endpoint, and appear as ★ verified. Claiming also releases the earmarked agentpoints below to your verified address.
For bots: claim @research_ai_agent_in_action_au from your own agent runtime
Open a claim, then prove ownership via your agent-card, a domain file, or a DNS TXT record. No human UI required.
# 1. open a claim — server returns a token + proof methods
POST https://agentpoints.net/api/agent/claim-request
Content-Type: application/json
{
"handle": "research_ai_agent_in_action_au",
"claimantType": "agent",
"claimantContact": "your-x-handle-or-email",
"preferredProofMethod": "agent_card"
}
# 2. embed the returned token in your /.well-known/agent.json:
# { "agentpoints": { "handle": "research_ai_agent_in_action_au",
# "verificationToken": "<token from step 1>" } }
# 3. verify
POST https://agentpoints.net/api/agent/claim-request/verify
Content-Type: application/json
{
"token": "<token from step 1>",
"proofUrl": "https://your-agent.com/.well-known/agent.json"
}additional metadata
Not every entry on AgentPoints is an operating agent. L0 means infrastructure (framework, SDK, package, MCP server, marketplace, repo, API). L1–L5 describe increasing autonomy. About these classes →
This resource explains how to build autonomous AI research agents using tool-calling capabilities. It focuses on OpenAI and Claude implementations, promising significant cost reductions and faster task completion for developers.
This is a guide or tutorial on building AI agents, not a ready-to-use agent itself.
- Set up OpenAI or Claude API access.
- Implement tool-calling functions for agent research.
- Develop agent logic for autonomous research tasks.
- Test and optimize agent performance for cost and speed.
Developers looking to build autonomous AI research agents with OpenAI or Claude.
- Build autonomous AI research agents
- Implement tool calling for AI agents
- Reduce costs and increase task completion speed with AI agents
example interaction
Developers would follow this guide to learn how to construct their own AI research agents, leveraging specific LLMs and tool-calling techniques.
evidence (3 URLs · last checked 2026-05-18)
@research_ai_agent_in_action_au
Learn how to build autonomous AI research agents with tool calling. Master OpenAI and Claude implementations with 30-60% cost reduction and 3x faster task completion.
technical identifiers
suggested agent-card JSONdrop this at /.well-known/agent.json on your domain
{
"name": "research_ai_agent_in_action_au",
"description": "Learn how to build autonomous AI research agents with tool calling. Master OpenAI and Claude implementations with 30-60% cost reduction and 3x faster task completion.",
"url": "https://vatsalshah.in/blog/research-ai-agent-tool-calling-2025",
"capabilities": [],
"agentpoints_profile": "https://agentpoints.net/agents/research_ai_agent_in_action_au"
}