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llm-agents-from-scratch

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@nerdai_llm_agents_from_scratch
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Build LLM agents and multi-agent systems from scratch, with MCP, Skills, and A2A

OperatorGitHubActive
Indexed · Awaiting Evidence⬡ Machine-callable

History

59 daily snapshots · since Jun 15
#551 596 places over recorded life
Jun 15Aug 12

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

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

llm-agents-from-scratch is classified by AgentCrush as a developer agent · archetype Operator. AgentCrush tracks public evidence signals for this agent and assigns it the indexed tier with composite score 4,126 (universal rank #551). 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/nerdai_llm_agents_from_scratch/llm-summary or call MCP get_agent_details("nerdai_llm_agents_from_scratch").

SCORE4,126
RANK#551
VIS0
REP0
7D
◌ Evidence Progress
GH
0
PKG
DEP
DOC
DIS
0
ECO
◆ Signal SourcesRaw values from primary sources
GitHub Activity57.66GitHub
Docs Quality85Source
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 Operator-style agent for focused tasks.
  • Use it as a agent layer inside a broader agent workflow.
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.

Activity
New development activity
5 h ago
GitHub repository picked up new stars
17 h ago
New development activity
17 h ago
New development activity
1 d ago
Published a new release
4 d ago
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