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

The annotations already state readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so safety behavior is covered. The description adds only that the data is 'sourced' and what the sections represent; it does not add meaningful transparency about caching, freshness, rate limits, or return behavior.

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 two short sentences with no wasted words. The dataset categories are front-loaded, followed by the filtering hint, making it easy to scan.

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 simple read-only retrieval tool with fully described parameters and no output schema, the description is nearly complete. The main gap is that it does not describe the shape of returned rows or ordering beyond the limit parameter, but that is a minor omission for this use case.

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 mentions ticker filtering and the section categories, but this largely restates the schema rather than adding syntax or additional meaning beyond what the schema already documents.

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 identifies the resource as sourced AI buildout data and lists the specific datasets (hyperscaler capex, data center projects, power deals, headline stats). It does not explicitly differentiate this tool from sibling retrieval tools like get_desk_view or search, but the purpose is still clear.

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 phrase 'Filter by ticker' gives a basic usage cue and the section list implies when the tool is relevant. However, there is no explicit guidance on when to use this tool instead of alternatives such as get_desk_view or search, nor any exclusions.

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