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sucesio-mcp

nponette/sucesio-mcp

87

Dominant

12 tools · Source: smithery · Scanned: May 11, 2026

Score breakdown

Findability

23/25

Can AI agents discover this tool? Measures naming quality, keyword overlap with queries, and registry presence.

Clarity

32/35

Can agents understand what this tool does? Measures description quality, action verbs, usage context ("Use this when..."), and return value documentation.

Precision

18/25

Is the interface precise? Measures input schema completeness, type definitions, required fields, enums, defaults, and parameter descriptions.

Efficiency

15/15

Is the tool token-efficient? Measures description length optimization, tool count, and naming conciseness.

Optimization status

All

This server is well-optimized for AI agent discovery. Consider adding enums, defaults, and usage examples for marginal gains.

Expected impact: +1-2 pts

Estimated selection rate

~85%

At 87/100, AI agents select tools like this approximately 85% of the time when choosing between competing alternatives. This server is in the top tier for agent discoverability.

Based on 500-round selection simulation (Pearson r = 0.828). Methodology →

Trust Verification

1Spec Verified
📋Spec Verified✓ Verified
87/100Spec Score
RequirementScore ≥ 85 on ToolRank Spec Quality analysis
MethodAutomated static analysis of tool definitions, descriptions, parameters, error handling
RenewalRe-verified on every scan (weekly)
🎯Selection Verified○ Not yet
—Win Rate
RequirementSelection win rate ≥ 70% in 100-round LLM tournament
MethodClaude Sonnet selects best tool for realistic tasks vs. competing servers
RenewalRe-tested monthly; expires if win rate drops below 60%
⚡Runtime Verified○ Not yet
—Status
RequirementTask success rate ≥ 90%, error rate < 5%, avg latency < 2s
MethodEnd-to-end execution tests in sandboxed environment
RenewalContinuously monitored; revoked on sustained failure
View full audit log → ![Trust](https://mcp.toolrank.dev/api/trust-badge/15d1346e-5030-4e82-9ae9-cadb15bc4136.svg)

Score history

87
Apr 19
87
Apr 20
87
Apr 21
87
Apr 22
87
Apr 23
87
Apr 24
87
Apr 25
87
Apr 26
87
Apr 27
87
Apr 28
87
Apr 29
87
Apr 30
87
May 1
87
May 2
87
May 3
87
May 4
87
May 5
87
May 6
87
May 7
87
May 8
87
May 9
87
May 10
87
May 11

Tracked daily. 23 data points.

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