F
licenseNot graded
qualityC
maintenanceEnables AI coding agents to consult a multi-model deliberation council before irreversible, high-stakes decisions, returning structured architectural decision records with consensus and dissenting risks.
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tokonomix-council-mcp
Officialby TokonoMix
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TDQS
A4.4/5.0
Scored across 11 tools
Disambiguation5/5
Each tool has a uniquely defined purpose: balance check, single vs consensus asks, model listing, skill version/content, onboarding steps, rating, human feedback, and context upload. The two ask tools are clearly differentiated by consensus vs single-model mode, and the two feedback tools separate agent rating from human relay. No overlap or ambiguity exists.
Naming Consistency4/5
All tools share the tokonomix_ prefix and snake_case, with most following a verb_noun pattern (get_balance, list_models, rate_consensus, relay_human_feedback). Minor deviations include skill_version (noun_verb) and onboard_verify (compound verb), but the overall pattern remains predictable and readable.
Tool Count5/5
At 11 tools, the set is well-scoped for its purpose: onboarding, billing, model discovery, request execution, context staging, feedback, and self-documentation. Each tool earns its place without redundancy or bloat, and the count aligns with typical MCP servers.
Completeness5/5
The toolset covers the full user lifecycle: onboarding (onboard/verify), account status (get_balance), model discovery (list_models), calling (single/consensus ask), large-context upload, and both human and agent feedback loops. It also includes a self-updating skill doc, and no obvious operational gaps exist for the stated purpose.
Maintenance
ActivityMaintained
ResponsivenessNo issues