Auto-Deep-Research vs OpenClaw Agents
Compare ranking, evidence, ecosystem context, and trust signals.
◆ AI-readable summaryJSON →
AgentCrush compares Auto-Deep-Research 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=hkuds_auto_deep_research,openclaw or MCP compare_agents(["hkuds_auto_deep_research","openclaw"]).
A
Auto-Deep-Research
@hkuds_auto_deep_research
Evidence RankedResearcher#870
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OpenClaw Agents
@openclaw
Evidence RankedOperator#3
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Score & Rank
Score
21.65
Rank
#870
7d Change
—
Score
70.93
Rank
#3
7d Change
+19
Evidence Signals
GitHub53.36
Packages—
Deps—
Docs33
Discourse—
Ecosystem—
Coverage: low
GitHub88
Packages100
Deps88
Docs84
Discourse30.66
Ecosystem5.68
Coverage: high
Trust Context
Evidence Ranked
No ERC-8004 registration matched
Evidence Ranked
No ERC-8004 registration matched
30-day Trend
→ Flat
Rank: #862 → #862
Score: 1622 → 21.65
1 days tracked
→ Flat
Rank: #3 → #3
Score: 9238 → 70.93
1 days tracked
Recent Signals
Repo spike3d ago
Repo spike4d ago
Repo spike15d ago
Repo spike17d ago
Repo spike19d ago
Dev activity162d ago
Repo spike162d ago
Dev activity163d ago
Repo spike163d ago
Dev activity163d ago