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 real value beyond that: result ordering ('best matches first') and the shape of each entry (platforms, input cells, preview image, page link). It does not mention pagination or how many results come back, which is the only notable gap.

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, then the entry shape, then the hand-off to get_model in a short final sentence. The long parenthetical model list is dense but earns its place by giving the agent vocabulary for matching user requests; otherwise the text is tight.

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 and the description wisely describes entry contents rather than duplicating the schema. However, for a search-style tool whose two inputs are undocumented at 0% coverage, the definition omits how to query and how many to request, which an agent needs to call it well.

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 0%, so the description carries the burden for the two parameters, yet neither 'query' nor 'limit' is mentioned. 'Best matches first' hints that relevance ranking exists but never explains that query is a search term or that limit caps result count, leaving an agent to guess from names alone.

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 ('List SheetsFinance's published, ready-made spreadsheet models') and backs it with concrete examples (DCF valuation, WACC, DuPont, ETF analysis), plus the ordering rule 'best matches first'. It also distinguishes itself from the sibling get_model by naming that tool's different job.

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?

Explicitly routes the agent: browse here, then 'Use get_model to hand one to the user.' That is a clear when-to-use and when-to-use-something-else signal. It stops short of saying when NOT to browse (e.g., when the user already knows the model name or wants docs_search instead), so it is not a full 5.

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