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Glama

canton-ccpedia

by io.github.UnityNodes

diagnose_error

Read-onlyIdempotent

Paste a Canton/Daml/Splice ERROR MESSAGE, stack trace, or error code and get the most likely resolved fixes from CCPEDIA history: forum threads where the same error was discussed, and related GitHub issues (each with its own date). Needs a literal error string or code (e.g. TOPOLOGY_TOO_MANY_PENDING_TOPOLOGY_TRANSACTIONS, ValidatorLicense); do NOT use it for symptom descriptions with no error text (e.g. "my balance is zero"), use semantic_search for those. Canton-specific. Returns top 3 matches each from forum and github.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax matches per source (default 3).
error_textYesError message, stack trace, or status code. Longer/more distinctive text returns better matches.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context about the data sources (CCPEDIA history, forum threads, GitHub issues with dates) and return count (top 3 from each). This goes beyond the annotations without contradicting them.

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?

The description is appropriately sized, front-loaded with the core action, and every sentence adds value: main purpose, examples, exclusions, and return format. No wasted words.

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?

With no output schema, the description explains return behavior (top 3 matches from forum and github). It covers the primary use case and limitations, though 'CCPEDIA' is not explained and could be clearer for an agent unfamiliar with the term.

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%, so the schema fully defines both parameters. The description adds some examples (e.g., TOPOLOGY_TOO_MANY_PENDING_TOPOLOGY_TRANSACTIONS) but largely repeats schema info. 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's purpose: paste an error message and get resolved fixes from forum threads and GitHub issues. It distinguishes from siblings by explicitly contrasting with semantic_search for symptom descriptions without error text.

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?

Explicit when-to-use guidance is provided: requires a literal error string or code, and explicitly says do NOT use for symptom descriptions, recommending semantic_search as an alternative. Also notes Canton-specific scope.

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