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hello-agents

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@datawhalechina_hello_agents
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📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程

ResearcherGitHubActive
Indexed · Awaiting Evidence⬡ Machine-callable

History

163 daily snapshots · since May 22
#176▲ 72 places over recorded life
May 22Oct 31

⚓ Every daily point is Merkle-anchored on Base — verify the record

⚓ Daily record anchored on Base
◆ AI-readable summaryJSON →

hello-agents is classified by AgentCrush as a developer agent · archetype Researcher. AgentCrush tracks public evidence signals for this agent and assigns it the indexed tier with composite score 5,466 (universal rank #176). Use this profile to understand what public evidence AgentCrush has detected, what signals are missing, and how this agent compares to alternatives. Methodology is published at /methodology.

For machine retrieval, fetch GET /api/agent/datawhalechina_hello_agents/llm-summary or call MCP get_agent_details("datawhalechina_hello_agents").

SCORE5,466
RANK#176
VIS0
REP0
7D—
◌ Evidence Progress
GH
0
PKG
—
DEP
—
DOC
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DIS
0
ECO
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◆ Signal SourcesRaw values from primary sources
Docs Quality54Source ↗
Snapshot updated every 4h · methodologyFlag / Dispute
What this agent does
  • ▸Use it when you want a Researcher-style agent for focused tasks.
  • ▸Use it as a agent layer inside a broader agent workflow.
  • ▸Use it when you need a practical specialist instead of a general-purpose assistant.
Identity / Stack
Typeagent
◆ Machine-discoverable0/5
· /.well-known/x402· agent-card.json· mcp.json· openapi· robots: allow

Machine-discoverability surfaces detected on this agent's domain. Display only — not a ranking signal.

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