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

Annotations already declare safe, idempotent, read-only behavior. The description adds value by describing the output contents ('dates, plain-language summaries, penalties, and links to the official regulator source') and notes cases are 'verified', giving the agent confidence in result trustworthiness. It does not contradict 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?

Four sentences, each earning its place: purpose, when-to-use, output summary, and next-step routing. The most important information is front-loaded and there is zero filler or redundancy.

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 the output schema exists, the description covers everything an agent needs: what the tool does, when to use it, what it returns, and how to proceed for full details. No gaps in context or decision-making.

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 coverage is 100% and every parameter has a clear description with examples, so the baseline is 3. The description adds domain context (Law 25 vs PIPEDA, regulators) that helps interpret the query/regulator params, but it doesn't add syntax or format details beyond what the schema already provides.

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 ('Search'), a resource ('verified Canadian privacy enforcement actions'), and scope ('CAI orders and decisions under Quebec Law 25 and OPC findings under PIPEDA'). It clearly distinguishes from the sibling tool by naming privacy_get_enforcement_case and explaining the division of labor ('Start here to find a case ID, then call...').

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?

It gives explicit when-to-use guidance: 'Use this when someone asks about privacy fines, enforcement cases against a company, what regulators decided, or investigations' with concrete example queries. It also tells the agent the next step (get full details via sibling), so routing is unambiguous.

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