Convenience wrapper: SV operations in the next N days, all environments, all operation types. Canton-specific. Quick "what should I be ready for this week?" answer for validator/SV ops.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Days ahead to look (1-180, default 30). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / days / defaultAdded value: +30Input schema / properties / days / descriptionPrevious value: -"Days ahead to look (1-180)."New value: +"Days ahead to look (1-180, default 30)."Input schema / requiredRemoved value: -[
- "days"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so baseline safety is known. Description adds context about being a convenience wrapper with full scope (all environments/types), but doesn't disclose return format or pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences deliver purpose, scope, and intended use without filler. Front-loaded with 'Convenience wrapper' and efficient phrasing, though 'Canton-specific' is a fragment.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only single-parameter tool, description provides enough intent but lacks explanation of output structure or what constitutes an 'operation' in this context. No output schema exists, so description could better clarify return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema fully documents the single 'days' parameter with range and default. Description's 'next N days' aligns with the schema but adds no new semantics beyond the schema's own description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly identifies tool as a convenience wrapper for SV operations within a time window, explicitly mentioning 'next N days', 'all environments', and 'all operation types'. It distinguishes from siblings by emphasizing broad scope and Canton-specific nature, though it doesn't name specific alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use-case: 'Quick "what should I be ready for this week?" answer for validator/SV ops', giving clear context for when to invoke. Does not mention alternatives or exclusions, but the intended scenario is well defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.