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

Annotations already declare readOnly, idempotent, non-destructive behavior, so safety is covered. The description adds substantive context beyond that: the return shape ('top 3 matches each from forum and github', dated) and the domain constraint ('Canton-specific'). It stops short of discussing match confidence or what happens on zero results, so a 4 rather than 5.

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?

Front-loads the purpose and the key input, then packs exclusions, scope, and return format into a dense but readable block. Every clause carries information; it is slightly long but not wasteful.

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?

With no output schema, the description supplies the return format itself (top 3 per source, dated, forum + github), plus input requirements and scope. An agent has everything needed to invoke and interpret results correctly.

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?

Schema coverage is 100%, so the baseline is 3, but the description earns extra credit by giving concrete error_text examples (TOPOLOGY_TOO_MANY_PENDING_TOPOLOGY_TRANSACTIONS, ValidatorLicense) that clarify what kind of literal input is expected. It doesn't document the limit parameter, but the schema already does.

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?

States a specific verb and resource ('diagnose' an 'ERROR MESSAGE, stack trace, or error code') and scopes it to Canton/Daml/Splice, which clearly distinguishes it from generic search siblings. An agent can tell it apart from semantic_search without opening either schema.

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?

Gives explicit when-to-use (literal error string or code) and when-NOT-to-use ('do NOT use it for symptom descriptions with no error text'), naming the alternative tool semantic_search for the excluded case. Nothing is left to inference.

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