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 useful behavioral context: it returns items with id, title, and url, and instructs to use the fetch tool for full details. This chaining behavior and the integration context go beyond what annotations provide, 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.

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

The description is concise, with four short sentences that each serve a purpose: state the search scope, describe the return format, explain the fetch chaining, and mention the integrations. It is front-loaded with the primary action and avoids any fluff or redundancy.

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?

The description covers the tool's search scope, return items, chaining to fetch, and integration use cases, while the output schema handles return details and annotations cover safety. It is missing only an explicit distinction from the sibling search_expenses and search_knowledge tools, which would enhance completeness but is not strictly necessary given the broad-scope description.

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 has 100% coverage with a clear description and example for the 'query' parameter. The tool description itself does not add additional parameter meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 searches the user's ExpenseBot data across expenses, reports, and knowledge base. The verb 'search' and the three explicit resource categories give a specific, unambiguous purpose. This broad scope distinguishes it from narrower siblings like search_expenses and search_knowledge, even though those alternatives are not named.

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 clear context for when to use this tool: to search across multiple data types and to power Deep Research and Company Knowledge integrations. It also gives a chaining instruction to use the returned id with the `fetch` tool for details. However, it does not explicitly mention when NOT to use it or name alternatives like search_expenses or search_knowledge, so it falls short of full exclusion guidance.

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