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

With no annotations, the description carries the behavioral disclosure burden and does so reasonably well. It reveals that requests are stored privately, that the purpose is product research, and that contact_uri is never automatically invoked. This goes beyond a generic 'request' statement and gives the agent useful non-obvious 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 sentences with no filler. It front-loads the primary purpose and adds the most important privacy/contact caveat right after. Every sentence carries meaningful information.

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 tool with seven parameters and no annotated descriptions, the description is too sparse to fully support correct invocation. The output schema exists, which lessens the need to explain return values, but the description leaves parameter semantics and selection guidance largely uncovered. It captures the high-level intent but not enough operational detail.

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 0%, so the description should compensate by explaining parameter meanings. It only explains contact_uri's optionality and non-auto-call behavior, and implicitly points at job_to_be_done. It provides no guidance for max_budget_usd, decision_criteria, current_alternative, max_latency_seconds, or required_output_fields, which are not self-explanatory.

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 a clear purpose: submit a structured request for a machine-service capability the agent would pay for. It names the core action and resource ('Tell the operator about a machine-service capability') and the context of product research. It does not explicitly differentiate from siblings, but sibling names are about payments/quotes, so the distinction is apparent.

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 useful context for when to use the tool: it is for capability requests the agent would pay for, stored for product research. It also clarifies that contact_uri is optional and never called automatically, which is a meaningful usage caveat. However, it does not state explicit when-not-to-use conditions or alternatives, leaving some inference required.

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