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Glama

canton-ccpedia

by io.github.UnityNodes

detect_builder_overlap

Read-onlyIdempotent

Given a project/proposal idea, find existing Canton ecosystem projects + dev-fund proposals that look similar: across BOTH the canton-dev-fund proposals corpus AND ecosystem_projects. Broader than find_similar_projects, which only searches the live ecosystem directory. Canton-specific. Cuts manual cross-reference research before submitting a new proposal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ideaYesOne-paragraph project idea or capability description.

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds context that the tool searches two corpora and is Canton-specific, which is useful but not extensive behavioral detail beyond what structured fields provide.

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

Conciseness4/5

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

The description is four sentences that each add value: purpose, sibling differentiation, scope, and usage context. It is not overly long, though the phrase 'across BOTH the canton-dev-fund proposals corpus AND ecosystem_projects' could be slightly shortened. Overall, it is well-structured and front-loaded.

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

Completeness4/5

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

Given one input parameter with full schema coverage, strong annotations, and sibling context, the description covers purpose, scope, differentiation, and usage scenario. It does not describe output format, but the tool's purpose (finding similar projects) implies a list of results, which may be acceptable. It is mostly complete for an AI to understand when and how to use the tool.

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% with a clear description of the 'idea' parameter as 'One-paragraph project idea or capability description.' The tool's description does not add additional parameter information beyond the schema, so 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 clearly states the tool finds similar projects across two specific corpora (dev-fund proposals and ecosystem projects) and explicitly contrasts with sibling find_similar_projects, which only searches the live directory. It provides a specific verb ('find'), resource ('Canton ecosystem projects + dev-fund proposals'), and scope ('Canton-specific').

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?

The description explicitly says this tool is 'Broader than find_similar_projects' and clarifies when to use it ('before submitting a new proposal'). It names the alternative tool and its limitation, giving clear guidance on when to choose this tool over find_similar_projects.

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