List infrastructure LoS targets

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the description goes well beyond them by disclosing the derivation model (base target per class/metric adjusted by criticality tier, with a worked example), that derived targets stay on the metric scale, that average risk is unavailable for infrastructure, and that none of the values are money. This is genuinely useful interpretive context for a read tool with no output schema.

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 purpose is front-loaded and no sentence is pure filler, but the paragraph is dense and heavily weighted toward derivation math (multiplier example, scale guarantees) that is tangential to invoking a filtered list. It reads more like data-model documentation than tool guidance.

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 output schema, the description does the work of explaining what the records represent and how to read their values, which is the key gap for this tool. It stops short of describing the response/pagination shape, though the schema notes automatic paging.

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 100%, so the baseline would be 3, but the description adds meaning over the bare enum by defining each metric's range and direction (fci 0-100 percent lower-is-better, asset_condition_avg higher-is-better read with fixed condition bands, asset_past_useful_life_pct lower-is-better) and by confirming the three filterable dimensions.

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?

States a specific verb and resource ('List technical Level of Service targets for infrastructure') and immediately narrows scope to 'one base target per feature class and metric'. An agent understands what is returned, but there is no explicit differentiation from the closely named siblings list_system_los_targets, list_los_proposed_targets, or get_infrastructure_los_target.

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 closing 'Filter by feature class, metric or active' implies the intended usage pattern, but the description never states when to choose this listing over list_system_los_targets or get_infrastructure_los_target, and gives no exclusions or prerequisites.

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