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canton-ccpedia

by io.github.UnityNodes

get_cip_votes

Read-onlyIdempotent

Get the cip-vote mailing-list messages for a specific Canton Improvement Proposal (CIP), oldest first: the raw discussion trail as sent, with each SV/participant's vote stated in their message body ("… votes in favor / not in favor"). This is the message thread, NOT a pre-computed count; the first message is usually the proposal announcement, not a vote. For the on-chain accept/reject tally use get_cip_vote_outcome. Use for reading who said what on Governance-type CIPs. Not the attachment PDFs (get_cip_attachments) or status timeline (get_cip_history). Canton ecosystem only. Not Cardano or other 'CIP' schemes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many messages (oldest first) to return. Default 25, max 100. The header states the full count and the range shown.
cip_idYesCIP id, e.g. "0117", "0118", or "CIP-0117". Numeric form preferred.
offsetNoSkip this many messages before returning, for paging through a long vote thread.

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / limit
      Added value: +{
+  "default": 25,
+  "description": "How many messages (oldest first) to return. Default 25, max 100. The header states the full count and the range shown.",
+  "maximum": 100,
+  "minimum": 1,
+  "type": "integer"
+}
    • addedInput schema / properties / offset
      Added value: +{
+  "default": 0,
+  "description": "Skip this many messages before returning, for paging through a long vote thread.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond this: it explains the raw nature of the thread, that the first message is usually the announcement rather than a vote, and that each SV's vote is within the message body. This clarifies what the tool returns and how to interpret it, which annotations alone do not convey.

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?

Four sentences, each earning its place: definition, distinction from count, alternative tool, and exclusions. Front-loaded with the core purpose and scope. No fluff or repetition.

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?

With no output schema, the description must convey what is returned. It does so clearly: 'raw discussion trail as sent' with each participant's vote in the body. It also covers scope (Canton ecosystem), ordering (oldest first), and what not to expect (not a count). Given the tool's moderate complexity (3 params, no output schema), the description is fully sufficient.

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 description coverage is 100% — all three parameters (cip_id, limit, offset) have clear descriptions including defaults, ranges, and semantics. The description does not add parameter-specific detail beyond what the schema provides; it only hints at ordering ('oldest first') which the schema also states. Baseline 3 is appropriate.

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 opens with a specific verb+resource: 'Get the cip-vote mailing-list messages for a specific Canton Improvement Proposal (CIP), oldest first.' It clearly distinguishes from siblings by explicitly stating it is NOT a pre-computed count, and points to get_cip_vote_outcome for the tally, get_cip_attachments for PDFs, and get_cip_history for the timeline.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'Use for reading who said what on Governance-type CIPs.' Provides clear exclusions: 'Not the attachment PDFs... or status timeline... Canton ecosystem only. Not Cardano or other CIP schemes.' Names an alternative tool for a different need: 'For the on-chain accept/reject tally use get_cip_vote_outcome.'

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

All canton-ccpedia toolsInspect
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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