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

With no annotations, the description carries the full burden. It discloses the nature of the output (structured event clusters with specific fields), the scoping behavior, and explicitly states exclusions (no republished text, no trading signal or probability estimate). This is valuable behavioral context beyond the schema. It does not mention authentication or rate limits, but those are implied by the api_key parameter in the schema, so the absence is acceptable.

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 a single, well-structured paragraph. It front-loads the primary purpose, then the scoping option, and finishes with clarifying exclusions. Every sentence adds value, with no redundant fluff. Appropriate length for the tool's complexity.

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 has no output schema, the description compensates by detailing what the output contains (entity/sentiment/quant-context fields, narrative summary) and what it excludes. It also explains scoping behavior. Missing are details about return format (e.g., list vs object), pagination, or error handling, but for a read-only feed tool this is sufficient for an agent to understand the purpose and expected result.

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 the description does not need to add parameter details. The description does mention 'Optionally scoped to one ticker' which maps to the ticker parameter, but that is already documented in the schema. No additional semantic value is provided for lang, limit, api_key, or marketplace_license_key, so 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 ('Get') and resource ('AI-structured event clusters from recent news'), and details the output composition (headline clusters with entity/sentiment/quant-context fields and an AI-written narrative summary). It explicitly distinguishes itself from sibling tools by clarifying it is structured fact extraction, not republished article text, and never includes a directional trading signal or probability estimate – clear differentiation.

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?

Provides clear context for when to use: optionally scoped to one ticker, otherwise returns the cross-market feed. The disclaimer about not being republished text and lacking trading signals implicitly tells the agent not to use this for raw articles or signal generation. However, it does not explicitly name sibling tools as alternatives or state when-not-to-use conditions, so it stops short of a 5.

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