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PCLA

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@masoudjtehrani_pcla
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PCLA: A framework for testing autonomous agents in the CARLA simulator

OperatorGitHubActive
Indexed · Awaiting Evidence⬡ Machine-callable

History

66 daily snapshots · since May 22
#592 542 places over recorded life
Jun 15Jul 26

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

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

PCLA 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 3,984 (universal rank #592). 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/masoudjtehrani_pcla/llm-summary or call MCP get_agent_details("masoudjtehrani_pcla").

SCORE3,984
RANK#592
VIS0
REP0
7D
◌ Evidence Progress
GH
0
PKG
DEP
DOC
DIS
0
ECO
◆ Signal SourcesRaw values from primary sources
GitHub Activity51.16GitHub
Snapshot updated every 4h · methodologyFlag / Dispute
What this agent does
  • Use it when you need tooling, infrastructure, or a base layer for other agents.
  • 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
2 d ago
New development activity
3 d ago
GitHub repository picked up new stars
5 d ago
New development activity
6 d ago
New development activity
6 d ago
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