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

The description goes beyond the annotations by disclosing important behavioral traits: it 'Costs credits', requires a specific prerequisite ('at least 5 strong edges'), and explains the process ('Profiles your strategies, searches today's news...'). It also describes the output format with '↳ lines'. These details are not present in the annotations and add significant transparency.

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 concise and well-structured: the first sentence gives the main purpose, the second explains the output detail, and the third states prerequisites and cost. Every sentence adds value, and there is no wasted text.

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 that the tool has no parameters and an output schema exists, the description is complete. It covers the core behavior, prerequisites, cost, and what the user can expect in the output. No gaps are apparent.

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?

The tool has zero parameters, so the baseline for parameter semantics is 4. The description adds no param-specific information because there are no params, which is acceptable; schema coverage is 100% by default.

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's function: 'Get a personalized market news briefing based on your validated edge library.' The verb 'get' plus the resource 'briefing' is specific and distinguishes it from sibling tools like general 'search' or 'varrd_ai'. It also explains the unique value proposition of tying headlines to the user's positions and edges.

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 for when to use the tool: it requires 'at least 5 strong edges in your library' and is intended for a personalized briefing. However, it does not explicitly mention alternatives or when not to use it, so it falls just short of the 'explicit when/when-not' benchmark.

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