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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safe read-only nature is covered. The description adds important behavioral context by stating it reads from a cache (not live data) and is CANTON-ONLY, which goes beyond the basic annotations. It does not describe error behavior or potential staleness, but the cache disclosure is valuable.

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?

The description is three sentences, each contributing critical information: the primary purpose, the cache/scope constraint, and the distinction from similar tools. It is front-loaded with the main action and avoids any filler, making it highly concise and well-structured.

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 single-item fetch tool with no output schema, the description covers the key aspects: what it returns (full body and comments), how to identify the item (GraphQL node ID), and important constraints (cached, CANTON-ONLY). It does not detail response structure or error handling, but given the tool's simplicity and the annotations, the description is largely complete.

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?

The input schema already provides a clear description for the 'id' parameter with an example. The description builds on this by indicating the ID comes from list_github_discussions, adding provenance that helps the agent understand how to obtain a valid value. With 100% schema coverage, the extra context earns a score above baseline.

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?

The description clearly states the tool retrieves the full body and comments of a single GitHub Discussion by its GraphQL node ID. It specifies the repo scope (Canton Network or Digital Asset) and differentiates from sibling tools like get_discussion and get_mailing_thread, making its purpose unambiguous.

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?

The description provides explicit usage context: it reads from CCPEDIA's cache, not the live GitHub API, and is restricted to Canton Network or Digital Asset repos. It also notes the ID must come from list_github_discussions and distinguishes from the web forum and mailing lists, effectively guiding when to use this tool versus alternatives.

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