message_timeline

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

With no annotations provided, the description carries the behavioral disclosure burden. It usefully discloses that the data comes from the local cache and that this is a read-only counting operation. However, it does not mention cache staleness, whether the cache is required, or any implications of missing/partial cached data.

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, front-loaded sentence with no wasted words. It conveys the core operation, resource, grouping, and data source efficiently.

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 counting tool, the description captures the main behavior, but there is no output schema and no annotation context. It could clarify the return shape, ordering, or treatment of empty periods, and it does not address possible ambiguity with analytics-related siblings.

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 schema already documents all four parameters. The description adds no meaning beyond the parameters, aside from reinforcing the hour/day grouping. This matches the baseline of 3 for fully documented schemas.

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 states a specific verb ('Get'), a precise resource ('message counts'), and the grouping dimension ('by time period (hour or day)'). It also names the source ('local cache'), which distinguishes it from remote search or analytics 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 phrase 'from the local cache' implies this is for cached message data, and the counting/grouping behavior implies a timeline analysis use case. However, it does not explicitly state when to prefer this over siblings like chat_analytics or today_messages, nor does it give exclusions or alternatives.

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