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pranaviate/statscan-mcp

90

Dominant

15 tools · Source: smithery · Scanned: May 6, 2026

Score breakdown

Findability

25/25

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

Clarity

33/35

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

Precision

17/25

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

Precision

Define required fields in your inputSchema to prevent agents from guessing parameters

Expected impact: +2-3 pts

Estimated selection rate

~85%

At 90/100, 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

0Unverified
📋Spec Verified○ Not yet
90/100Spec 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/2d3442d7-fc90-40cc-a394-31291891c548.svg)

Score history

90
Mar 28
90
Mar 28
90
Mar 29
90
Mar 29
90
Mar 29
90
Mar 30
90
Mar 31
90
Apr 1
90
Apr 2
90
Apr 3
90
Apr 4
90
Apr 5
90
Apr 6
90
Apr 7
90
Apr 8
90
Apr 9
90
Apr 11
90
Apr 12
90
Apr 13
90
Apr 14
90
Apr 15
90
Apr 16
90
Apr 17
90
Apr 18
90
Apr 22
90
Apr 23
90
Apr 24
90
Apr 25
90
Apr 26
90
Apr 27

Tracked daily. 30 data points.

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