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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely new behavior: results are org-agnostic, excerpts carry source links, and ranked feature-catalog entries precede documentation excerpts. It does not discuss result volume relative to the limit or relevance/ranking control, but it exceeds what the annotations convey.

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?

Three sentences, each doing distinct work: corpus definition, usage triggers, and result contract. The scope constraint and the return ordering are front-loaded where an agent will read them, and there is no filler or restatement of the tool name.

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?

An output schema exists, so return values need not be explained, and the description still adds the useful ordering detail. For a two-parameter read tool with full annotation coverage, everything needed for correct selection and invocation is present.

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 description coverage is 100%, so both the query and limit parameters are fully documented in the schema, including the limit default of 4 and the max of 10. The description adds no parameter-level guidance such as query phrasing tips or how the limit interacts with the two-tier result ordering, so the baseline of 3 applies.

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 opens with a specific verb and resource ('Search Spun product knowledge') and enumerates what the corpus contains: feature explanations, how-to steps, UI locations, and documentation excerpts with source links. It sharply limits scope to product documentation and excludes organization data and message content, which implicitly separates it from search_messages_and_contacts. It does not, however, distinguish itself from the similarly named kb_search sibling, which an agent could reasonably confuse with it.

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?

It gives concrete trigger phrasings ('how do I…', 'what is…', 'does Spun support…') plus a negative rule that it never returns org data or message content, which is a usable when/when-not signal. What is missing is an explicit named alternative — there is no instruction like 'for customer conversations use search_messages_and_contacts' or a statement of how this differs from kb_search.

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