autoresearch vs OpenClaw Agents
Compare ranking, evidence, ecosystem context, and trust signals.
◆ AI-readable summaryJSON →
AgentCrush compares autoresearch and OpenClaw Agents across public evidence signals — GitHub activity, package usage, dependency adoption, docs quality, ecosystem links, and discourse. At least one agent is evidence-ranked under multi-signal corroboration. The comparison shows evidence differences, not a universal winner. Methodology at /methodology.
For machine retrieval: GET /api/compare/llm-summary?agents=karpathy_autoresearch,openclaw or MCP compare_agents(["karpathy_autoresearch","openclaw"]).
a
autoresearch
@karpathy_autoresearch
Evidence RankedResearcher#947
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OpenClaw Agents
@openclaw
Indexed · Awaiting EvidenceOperator#3
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Score & Rank
Score
19.16
Rank
#947
7d Change
—
Score
9233
Rank
#3
7d Change
+19
Evidence Signals
GitHub—
Packages—
Deps—
Docs36
Discourse53.95
Ecosystem—
Coverage: low
Not evidence-ranked yet. How evidence ranking works →
Trust Context
Evidence Ranked
No ERC-8004 registration matched
Indexed · Awaiting Evidence
No ERC-8004 registration matched
30-day Trend
→ Flat
Rank: #726 → #726
Score: 2482 → 19.16
1 days tracked
→ Flat
Rank: #3 → #3
Score: 9233 → 9233
1 days tracked
Recent Signals
No recent signals
Dev activity73d ago
Repo spike73d ago
Dev activity73d ago
Repo spike73d ago
Dev activity73d ago