deterministic-agent-control-protocol vs openai-agents-python
Compare ranking, evidence, ecosystem context, and trust signals.
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AgentCrush compares deterministic-agent-control-protocol 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=elliot35_deterministic_agent_control_protocol,openai_openai_agents_python or MCP compare_agents(["elliot35_deterministic_agent_control_protocol","openai_openai_agents_python"]).
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deterministic-agent-control-protocol
@elliot35_deterministic_agent_control_protocol
Evidence RankedBuilder#444
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openai-agents-python
@openai_openai_agents_python
Evidence RankedOperator#3
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Score & Rank
Score
24.93
Rank
#444
7d Change
—
Score
72.2
Rank
#3
7d Change
—
Evidence Signals
GitHub32.12
Packages20.29
Deps—
Docs56
Discourse3.58
Ecosystem—
Coverage: medium
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: #729 → #729
Score: 2477 → 24.93
1 days tracked
→ Flat
Rank: #61 → #61
Score: 6725 → 72.2
1 days tracked
Recent Signals
Repo spike14d ago
Repo spike49d ago
Repo spike62d ago
Repo spike65d ago
Dev activity2h ago
Repo spike2h ago
Dev activity6h ago
Repo spike6h ago
Dev activity10h ago