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santiago.blanco.vilchez/santiago-cpa

88

Dominant

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

Score breakdown

Findability

25/25

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

Clarity

28/35

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

Precision

22/25

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

Efficiency

13/15

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

Optimization status

Clarity

Add "Use this when..." context to your description so agents know when to invoke this tool

Expected impact: +3-5 pts

Estimated selection rate

~85%

At 88/100, 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
88/100Spec 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/98e4ea62-81a7-4fea-a836-d8ae364d6756.svg)

Score history

88
Mar 28
88
Mar 28
88
Mar 29
88
Mar 29
88
Mar 29
88
Mar 30
88
Mar 31
88
Apr 1
88
Apr 2
88
Apr 3
88
Apr 4
88
Apr 5
88
Apr 6
88
Apr 8
88
Apr 9
88
Apr 11
88
Apr 12
88
Apr 13
88
Apr 14
88
Apr 15
88
Apr 16
88
Apr 17
88
Apr 18
88
Apr 19
88
Apr 20
88
Apr 21
88
Apr 22
88
Apr 25
88
Apr 26
88
May 3

Tracked daily. 30 data points.

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