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

Annotations already signal readOnly, idempotent, and non-destructive behavior. The description goes beyond annotations by revealing the 10-minute refresh cadence, the source (dchub news pipeline), the extraction method (regex for $-figures and MW), and actor classification. This gives the agent meaningful behavioral context without contradicting annotations.

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: scope, source/method, refresh behavior, use cases, and exclusions. Front-loading the core value proposition and then providing routing guidance makes it efficient and easy to parse.

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?

With a simple one-parameter schema, an output schema present, and annotations covering safety semantics, the description provides all needed operational context: what the feed is, how fresh it is, how it is built, and when not to use it. The final sentence explicitly reiterates the tool's identity as the live $1B+ AI-capex feed, closing any ambiguity.

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%, with the single 'limit' parameter fully documented in the schema. The description does not add parameter-specific detail, but none is needed given the schema already explains the parameter. 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?

The description clearly states this is a 'live feed' of hyperscaler AI deals, naming specific actors (Stargate, OpenAI, Anthropic, Microsoft, Oracle, etc.) and the source pipeline. It explicitly differentiates itself from siblings by naming list_transactions and deal_autopsy as alternatives, so an agent can distinguish it without opening schemas.

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 gives explicit use cases: tracking AI capex events, capacity announcements, and competitive intel. It also provides clear negative guidance with alternatives: 'Do NOT use for the full historical M&A comp set (use list_transactions) or a single-deal teardown with grid context (use deal_autopsy).' This is exemplary routing guidance.

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