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

With annotations already covering readOnly/idempotent/non-destructive/openWorld=false, the description still adds real behavioral context: the shape of results (stories, sides, tests, entities plus canonical URLs) and the negative-result behavior (a 'no formed side' answer with up to three nearest items explicitly labeled nearest). It does not mention pagination or result ordering, so 4 rather than 5.

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 routing condition is front-loaded in the opening clause and every clause carries information (trigger, return shape, fallback behavior, ordering rule). It is dense and semicolon-heavy, so it is slightly harder to scan than an ideal 5, but nothing is wasted.

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?

There is no output schema, so the description carries the burden of describing returns, and it does so including the graceful 'no formed side' fallback. Annotations cover the safety profile and the schema covers all parameters, leaving only minor unspecified details such as hit ranking or default behavior when kinds is omitted.

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 coverage is 100%, so query, kinds and limit are fully documented in the schema; the description's mention of companies/people/questions loosely echoes the query semantics. Baseline 3 applies because the description adds no syntax, format or constraint detail beyond the schema.

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 states what the tool retrieves (matching stories, sides, tests and entities with canonical URLs) and its domain (the AI economy / DeepStack's published analysis). It also implicitly distinguishes itself from slug-based siblings by saying to use it first when the slug or name is not known, though it never names a sibling tool explicitly.

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 a clear trigger (user asks where informed investors disagree, or wants published analysis on a company, person or question) and an ordering rule ('use it first when the slug or name is not known'). No explicit when-not-to-use or named alternative is provided, so it falls just short of the top band.

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