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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond the annotations: the tool does not classify, does not treat omitted answers as 'No', and requires no sign-in/private access. These are meaningful disclosures that help the agent set expectations.

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?

Four sentences, each earning its place: purpose, parameter handling, behavioral limits, and access constraints. The purpose is front-loaded in the first clause, and there is zero filler or repetition of annotation 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 single-optional-parameter read-only tool with safety annotations already provided, the description covers purpose, returns ('questions and explanations'), parameter semantics, and access limits. Minor gaps remain: the description never explains how the 'selected AI system' is established (e.g., prior session state or sibling tool output), and the fact keys are unspecified.

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 must compensate, and it does: 'Pass only known user answers; omit unknown values or use null' directly explains what the 'facts' object represents and how to populate it, aligning with the schema's allowance for null. It does not enumerate the fact keys, but it gives the parameter real semantic meaning beyond the raw schema.

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 specific verb and resource: 'Get relevant business questions and explanations for a selected AI system.' It also delimits scope with 'Does not classify,' which implicitly separates it from the screening sibling. However, it never names the sibling tools (merron_scan_project, merron_screen_ai_act) explicitly, so the differentiation is inferential rather than explicit.

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 clear invocation guidance ('Pass only known user answers; omit unknown values or use null') and a constraint ('No sign-in or private workspace access'), but it never states when to choose this tool over its siblings or when not to use it. The when-to-use context is implied by the tool name and the 'does not classify' remark rather than stated.

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