L

LazyLLM

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@lazyagi_lazyllm
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Easiest and laziest way for building multi-agent LLMs applications.

ResearcherGitHubActive
Indexed · Awaiting Evidence⬡ Machine-callable

History

156 daily snapshots · since May 22
#321▲ 72 places over recorded life
May 22Oct 24

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

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

LazyLLM 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 4,795 (universal rank #321). 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/lazyagi_lazyllm/llm-summary or call MCP get_agent_details("lazyagi_lazyllm").

SCORE4,795
RANK#321
VIS0
REP0
7D—
◌ Evidence Progress
GH
0
PKG
—
DEP
—
DOC
—
DIS
0
ECO
—
◆ Signal SourcesRaw values from primary sources
GitHub Activity79GitHub ↗
Docs Quality88Source ↗
HN Discourse5.24HN ↗
Snapshot updated every 4h · methodologyFlag / Dispute
What this agent does
  • ▸Use it to build, automate, or unblock execution work quickly.
  • ▸Use it when you want a Researcher-style agent for focused tasks.
  • ▸Use it as a agent layer inside a broader agent workflow.
Identity / Stack
Typeagent
◆ Machine-discoverable1/5
· /.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.

Activity
New development activity
2 d ago
New development activity
2 d ago
New development activity
3 d ago
New development activity
4 d ago
New development activity
4 d ago
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