Maze vs OpenClaw Agents
Compare ranking, evidence, ecosystem context, and trust signals.
◆ AI-readable summaryJSON →
AgentCrush compares Maze 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=maze_agent_maze,openclaw or MCP compare_agents(["maze_agent_maze","openclaw"]).
M
Maze
@maze_agent_maze
Evidence RankedOperator#797
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OpenClaw Agents
@openclaw
Evidence RankedOperator#2
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Score & Rank
Score
21.29
Rank
#797
7d Change
—
Score
72.59
Rank
#2
7d Change
+19
Evidence Signals
GitHub57.71
Packages—
Deps—
Docs—
Discourse—
Ecosystem—
Coverage: low
GitHub93
Packages100
Deps69.6
Docs84
Discourse63.27
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: #478 → #478
Score: 4392 → 21.29
1 days tracked
→ Flat
Rank: #3 → #3
Score: 9234 → 72.59
1 days tracked
Recent Signals
Repo spike3d ago
Dev activity3d ago
Dev activity5d ago
Dev activity9d ago
Dev activity9d ago
Dev activity88d ago
Repo spike88d ago
Dev activity88d ago
Repo spike88d ago
Dev activity88d ago