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

With no annotations, the description carries the full burden. It disclose the data scope (news_article columns), syntax (`tk='NVDA'`), time range, and aggregation support, which goes well beyond schema descriptions. It does not explicitly state read-only or return format, but 'search' implies read-only and the column listing provides expectations. The transparency is solid but not exhaustive.

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 dense but every sentence earns its place: archiving depth, plan availability, column list, ticker filtering syntax, example, and aggregation note. It is front-loaded with purpose and uses a practical example. No 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?

Given the tool's complexity (9 params, SQL interface, aggregation), the description covers the key aspects: query syntax, available columns, example, and aggregation. It doesn't explain default output shape, but schema covers defaults and cursor/pagination. The description is sufficiently complete for an agent to use it correctly, with minor gaps around response format.

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 baseline is 3. The description goes beyond schema by explaining the SQL WHERE pattern, the auto-unnest alias `tk`, and how group_by/having work together. This adds meaningful semantic value for the main parameters, especially `q` and `group_by`, without duplicating schema info.

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 a news archive with a SQL WHERE clause, a specific verb+resource. It distinguishes itself from sibling tools (e.g., tickerbot_get_ticker_bars, list_events) by focusing on news articles and even provides column details and an example query. The purpose is unmistakable.

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: searching news, archive back to 2015, and available on every plan. It gives a concrete example and mentions aggregation capabilities. It does not explicitly name alternative tools or exclusion criteria, but the context is strong enough for an agent to know when to use it. Missing explicit 'when not to use' guidance, but clear context earns a 4.

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