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

Annotations already cover read-only/idempotent/no-open-world safety, but the description adds meaningful behavior: results are capped at 10 matches, data is recomputed nightly from public filings and end-of-day prices, and it is explicitly not real-time. That freshness and result-cap context is the kind of thing annotations cannot express.

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, front-loaded with what the tool does, followed by return shape and then the data-freshness/disclaimer caveat. Every sentence carries information an agent needs; nothing is padding.

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 one-parameter search tool with no output schema, the description covers scope, input kinds, result count, the key return field, and data provenance. It stops short of describing zero-match or ambiguous-match behavior, which is a minor but real gap.

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% — the single 'query' parameter already documents ticker vs. partial-name usage with examples ('NVDA', 'BRK.B', 'nvidia') and length bounds. The description adds no syntax or format guidance beyond the schema, so the baseline 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?

States a specific verb (find) and resource (US stock covered by SweetValueLab), plus the exact universe (S&P 500 and Nasdaq-100 constituents) and the accepted lookup keys (ticker or company name). An agent can distinguish this from get_stock_valuation and get_market_context without opening any 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?

Explicitly names the downstream consumer of the result ('the ticker to pass to get_stock_valuation'), which implicitly tells the agent when to reach for this tool first. It also sets scope boundaries ('Not real-time quotes, not investment advice'), but never states the inverse case — e.g. what to do if the lookup fails or the stock isn't covered.

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