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canton-ccpedia

by io.github.UnityNodes

list_votes_by_sv

Read-onlyIdempotent

Get the on-chain voting record of Canton Super Validators: how many DSO governance votes each has cast, how often they voted for or against, how often they abstained, and the span of their participation. Use for 'how does Tradeweb vote', 'which SVs abstain most', 'who is most active in governance'. CCPEDIA-unique: derived from the full ledger vote history. Canton ecosystem only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sv_nameNoSuper Validator short name, e.g. "Tradeweb-Markets-1", "Digital-Asset-1", "Cumberland-1". Omit for all of them.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds 'derived from the full ledger vote history' (indicating computed data) and 'Canton ecosystem only' (scope). This adds moderate context but does not disclose potential performance or data freshness details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences: first states purpose, second gives example queries, third notes uniqueness and scope. No fluff; each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one optional parameter), rich annotations, and full schema coverage, the description covers what the tool returns (types of counts) and scope context. No output schema exists, but the description sufficiently informs the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and includes description for the single parameter 'sv_name'. The tool description repeats the parameter's purpose and examples, adding no new meaning beyond the schema. Baseline score of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and resource ('on-chain voting record of Canton Super Validators'). It provides clear example queries and distinguishes from siblings via 'CCPEDIA-unique: derived from the full ledger vote history' and 'Canton ecosystem only'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit use cases ('how does Tradeweb vote', etc.), implying when to use it for governance voting questions. However, it does not mention when not to use it or compare with sibling tools like 'get_governance_vote' or 'list_governance_votes', leaving ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.7/5.0
Disambiguation2/5

Many tools have overlapping search/retrieval functionality (search, semantic_search, full_context, search_community, search_github_issues, etc.), and the CIP-specific variants (get_cip, get_cip_history, get_cip_votes, get_cip_mentions, get_cip_citations) are numerous and subtly differentiated. Despite cross-references in the descriptions, the boundaries are fine-grained and an agent is likely to misselect among the 8+ search tools or the 8+ CIP tools.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (get_x, list_x, search_x, find_x). Mixed styles or camelCase are absent, and the verb choice (get, list, search, find, detect, compare) is semantically appropriate to each action, making the naming highly predictable.

Tool Count1/5

With 88 tools, the surface is extremely overgrown for a single server, far exceeding the 25+ 'too many' threshold and approaching the 50+ 'extreme mismatch' category. Even for a comprehensive ecosystem knowledge base, this creates a massive selection burden and makes the tool set unwieldy for agents.

Completeness5/5

The server covers the full Canton ecosystem: docs, forum, mailing lists, GitHub, CIPs, governance, validators, versions, deprecations, security, and media. There are no glaring gaps in the knowledge domain; every major resource type has retrieval and analysis tools, making the coverage exhaustive with no obvious dead ends.

Resources