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

With no annotations, the description carries the full burden. It discloses the output shape and that the result derives from the three sub-scores, implying a pure computation, but it does not state whether the operation is side-effect-free, how the sub-scores are weighted, or what thresholds produce each badge.

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 a single concise sentence with no filler. The output is front-loaded, and the input list is clearly and completely stated.

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 simple three-input deterministic computation, the description covers the essential input/output contract, especially since it names the score and badge despite the lack of an output schema. Minor gaps remain around exact output formatting and badge thresholds.

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. It groups the three parameters as 'news, pain, hiring' and gives the 0-10 range, but it does not define the meaning of each signal score beyond what the parameter names already convey.

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 verb ('Compose'), the exact output ('composite_urgency_score' with 0-10 range and badge levels), and the three inputs. This distinguishes it from sibling compute_* tools by naming the urgency-specific result and badge.

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 explicit guidance on when to use this tool versus the many sibling compute_* tools, such as compute_lrs_composite or compute_collection_scores. The phrase 'from 3 sub-scores' implies the prerequisite inputs, but no alternatives or exclusions are mentioned.

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