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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds the meaningful context that the dataset is scoped to the Netherlands and aggregates both service outages and grid-operator utility outages. It does not say how fresh the data is, whether results are aggregated per provider, or what the response shape looks like.

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?

A single sentence with no filler, front-loaded on the core concept (lopende storingen) followed by the covered domains. Nothing is wasted, though the parenthetical list carries most of the informational weight.

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 no parameters and no output schema, the description carries most of the burden and does cover the data's subject and geographic scope. It leaves gaps on freshness/cadence and result structure that matter for a live-status tool. Adequate but not complete.

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?

The tool takes zero parameters, so the baseline is 4 per the rubric. The description correctly implies a no-argument, snapshot-style call and does not mislead about filtering options.

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?

Names the resource precisely (ongoing outages) and enumerates the covered domains: internet, mobile, banks, public transport, plus power/gas outages from Dutch grid operators. An agent immediately knows what data comes back. It stops short of naming overlap with siblings such as 'internet', 'mobiele_markt' or 'energie_stand', so it is clear but not differentiated.

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?

There is no statement of when to call this versus the many adjacent siblings (internet, energie_stand, mobiele_markt) that plausibly surface overlapping information. The only hint is the word 'lopende' (current), which merely implies a real-time snapshot. No exclusions, no prerequisites, no alternatives.

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