Auto-Deep-Research vs openai-agents-python
Compare ranking, evidence, ecosystem context, and trust signals.
◆ AI-readable summaryJSON →
AgentCrush compares Auto-Deep-Research and openai-agents-python 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,openai_openai_agents_python or MCP compare_agents(["hkuds_auto_deep_research","openai_openai_agents_python"]).
A
Auto-Deep-Research
@hkuds_auto_deep_research
Evidence RankedResearcher#704
View profile →
o
openai-agents-python
@openai_openai_agents_python
Evidence RankedOperator#3
View profile →
Score & Rank
Score
21.98
Rank
#704
7d Change
—
Score
72.2
Rank
#3
7d Change
—
Evidence Signals
GitHub55.37
Packages—
Deps—
Docs33
Discourse—
Ecosystem—
Coverage: low
GitHub95.03
Packages100
Deps88.64
Docs74
Discourse22.8
Ecosystem—
Coverage: high
Trust Context
Evidence Ranked
No ERC-8004 registration matched
Evidence Ranked
No ERC-8004 registration matched
30-day Trend
→ Flat
Rank: #874 → #874
Score: 1600 → 21.98
1 days tracked
→ Flat
Rank: #61 → #61
Score: 6725 → 72.2
1 days tracked
Recent Signals
Repo spike2d ago
Repo spike3d ago
Repo spike4d ago
Repo spike4d ago
Repo spike8d ago
Dev activity1h ago
Dev activity5h ago
Repo spike9h ago
Repo spike13h ago
Dev activity17h ago