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Podcast Transcripts On-Demand

petabloom/podcasts

90

Dominant

5 tools · Source: smithery · Scanned: June 10, 2026

Score breakdown

Findability

25/25

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

Clarity

30/35

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

14/15

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 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/305d473c-97b2-4972-9a82-ec60566226e1.svg)

Score history

92
Apr 11
92
Apr 12
92
Apr 14
92
Apr 15
92
Apr 18
92
May 18
92
May 19
92
May 20
92
May 21
91
May 22
91
May 23
91
May 24
91
May 25
91
May 26
90
May 27
90
May 28
90
May 29
90
May 30
90
May 31
90
Jun 1
90
Jun 2
90
Jun 3
90
Jun 4
90
Jun 5
90
Jun 6
90
Jun 7
90
Jun 8
90
Jun 9
90
Jun 10

Tracked daily. 29 data points.

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