Causes

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so safety is covered. The description adds genuinely non-obvious behavior: results are ordered by the sequence in which rules are tried, values come from TfL's raw reason text, and a null cause means unknown. It doesn't say anything about whether the list is static or changes with TfL data updates, which would help an agent decide on caching.

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?

Two sentences, both carrying content: one defines the output and ordering, the other connects it to `disruptions` and handles the null case. It's front-loaded with the core definition. The phrasing 'puts disruptions down to' is informal internal jargon that costs a little parse time versus 'attributes disruptions to'.

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, no output schema and annotations covering the safety profile, the remaining burden is describing what comes back and how to use it — and the description does both, including ordering and the null/unknown convention. An agent has everything needed to call it correctly and interpret results.

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 there is nothing for the description to disambiguate and the baseline of 4 applies. The description does clarify the semantics of the related `cause` value consumed elsewhere, which is a useful adjunct but not a parameter explanation.

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 names a specific resource (the cause codes Tifa derives from TfL reason text) and states its shape (codes with labels) and ordering (rule-trial order). It distinguishes itself from siblings by tying directly to the `cause` field of `disruptions`. It lacks an explicit verb like 'list' or 'returns', relying on a noun phrase, which slightly blunts the statement of purpose.

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 a clear use context: these codes are what `disruptions` accepts as `cause`, and it explains the edge case that a null cause is unknown and `cause=unknown` finds those records. What's missing is an explicit statement of when to call this versus `disruptions` (e.g. 'call this first to discover valid filter values'), so the routing is implied rather than stated.

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