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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds substantial behavioral context beyond that: the verdict categories, the disclosed-vs-attributed roles comparison, inclusion of every recorded event with employer's own words and primary source, and the not-found behavior ('says so and what that does and does not mean'). No contradiction with 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?

Three sentences with a logical flow: framing question, detailed return contents, and edge-case behavior. The opening sentence slightly echoes the title but serves as a natural lead-in. The rest is information-dense with no wasted words, earning a high-but-not-perfect score.

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-parameter tool with no output schema, the description comprehensively covers the return contract (verdict, roles comparison, events, sources) and the not-found case. It doesn't specify the exact response format, but enumerating the result components is enough for an agent to understand the outcome. Minor ambiguity remains about whether 'roles' are counts or lists, but overall it's 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?

Schema coverage is 100% and the schema already explains the company parameter with examples and 'Partial names work.' The description only repeats that it accepts a company name like 'Klarna' or 'Salesforce,' adding no new parameter meaning. Baseline 3 is appropriate given full schema coverage.

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 the tool's function: 'Returns the register's verdict for that company (explicit, mixed or blamed), the roles it disclosed vs the roles counted as AI-attributed, and every recorded event.' The verb 'Returns' and the resource (per-company AI-layoff details) are specific, and the scope 'specific company' distinguishes it from the aggregation/search/index siblings.

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 establishes when to use the tool: when you have a specific company name ('Accepts a company name such as 'Klarna' or 'Salesforce'') and want a verdict for that company. It does not explicitly name alternatives or exclusions, but the context is clear enough that an agent could infer the right selection among siblings.

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